Automated Scheduling, Optimisation and Planning (ASAP) Research Group

School of Computer Science Automated Scheduling, Optimisation and Planning (ASAP) Research Group Research Report 2009-2011

Contents Welcome 3 The LANCS Initiative 4 Heuristic Understanding 5 Systems to Build Systems 5 Next Generation Decision SupportAutomating the heuristic design process 6 The Cross-domain Heuristic Search Challenge: An International Research Competition 8 Educational Timetabling 9 Sports Timetabling 10 Cutting and Packing 11 Improving Airportand Airline Operations 12 Personnel Rostering and Healthcare 14 Outreach 16 Conference Organisation 17 Spin Out Companies 18 Professional Activities 19 Publications (2009-2010) 24 Grants 34 ASAP Personnel 38 Visiting Fellows/Associate Staff 42 Former Members 42 How to Find Us 43 2 ASAP Automated Scheduling, Optimisation and Planning Research Group

Welcome Welcome to our 2009-2011 research report. Over this period, the Automated Scheduling, Optimisation and Planning (ASAP) group has strengthened its position as one of the leading research groups in the world in computational search methodologies. Throughout the period our aim was to set the following research directions on the international agenda: Modelling the complexity and uncertainty inherent in complex, real-world problems across a wide range of application areas including airport optimization, cutting and packing, educational timetabling, healthcare, network routing, personnel scheduling, portfolio optimization, production scheduling/rescheduling, public transport optimization, space allocation, transportation logistics optimization and vehicle routing. Developing intelligent systems that can automatically aid the design and implementation of more efficient, effective, reusable, easier-to-implement/deploy/use general computational search methods that are applicable to a range of real-world problems. Developing rigorous mathematical theories for a more profound understanding of real world problems and effective design of intelligent decision support systems. carrying out world leading research. One of the key motivations for Platform awards is to underpin internationally outstanding research teams by providing funding that can be flexibly managed to bridge the gaps between externally funded projects. ASAP were awarded a Platform Grant in 2004. In 2010, this grant was renewed to the value of just over 1M. This renewal of our platform funding recognises the international leadership of the group and provides the group with a level of financial stability that will enable us to address our key research themes over the next few years. We continue our research work on the EPSRC funded Science and Innovation Grant, LANCS, which supports collaboration between four leading Operational Research groups in the U.K. (Lancaster, Nottingham, Cardiff, Southampton). The launch of Staff Roster Solutions Ltd in 2010 saw the establishment of our third spin out company. This underlines our commitment to addressing scientific challenges that are derived from industrial requirement. We have published research results in many of the leading journals in the world in Operational Research and Computer Science. Our research achievements over this period are outlined in this report. Our expertise in Computer Science and Operational Research allows us to bring a unique and novel perspective to traditional Operational Research problems, and also to bring new real-world problems to the Computer Science community. Professor Edmund Burke left the group in December 2011 to take a new appointment as Pro-vice Chancellor for Research at the University of Stirling. His leadership of ASAP has been exemplary. Professor Sanja Petrovic moved into the role of the head of the group. The Engineering and Physical Sciences Research Council (EPSRC) funded Platform Grant will help further the group to continue We are very happy to provide more detail if you have any further questions. Our contact details are given at the end of the report. www.asap.cs.nott.ac.uk 3

The LANCS Initiative Green Logistics Transport Heuristic Understanding Research Themes Healthcare Systems to Build Systems Discrete and Nonlinear Optimisation The LANCS initiative research clusters The LANCS initiative collaborators The LANCS Initiative is a collaboration between four of the leading Operational Research (OR) groups in the UK. Specifically, the four universities involved are: LA Management School, Lancaster University N School of Computer Science, University of Nottingham C School of Mathematics, Cardiff University S School of Mathematics and School of Management, University of Southampton This collaboration represents a funding programme of over 13M. It is supported through the EPSRC s Science and Innovation initiative, with 5.4M being provided by EPSRC and the remainder from the four universities. As far as we are aware, this is the largest Operational Research grant in the world. The Initiative started in September 2008 and is expected to have a significant influence on the development of OR within the UK, and, indeed, across the world. According to EPSRC s 2004 International Review of OR, the UK has a strong position in the practical application of OR. However, in the wider community, there has generally been a gap between the theory and the practice. A primary goal of the LANCS Initiative is to close this gap, and to contribute towards building UK capacity in OR by setting the overall long-term national and international research agenda. That is, it has the aim of building the theory of OR in order to support the practice of OR. The LANCS initiative is organised around six research clusters. Two of these are concerned with application areas that are vital to the UK: Transport and Logistics, and Healthcare. The remaining four clusters are concerned with important theoretical research directions: Discrete Nonlinear Optimisation, Stochastic Modelling, Heuristic Understanding and Systems to Build Systems, with the last two being led by Nottingham. These two Nottingham-led themes are explored in more detail on the opposite page. It is important to note though that Nottingham plays a key role across the whole of the LANCS initiative. 4 ASAP Automated Scheduling, Optimisation and Planning Research Group

Heuristic Understanding Many real-world problems are too large for classical exact optimisation methods to be employed. However, good quality solutions can often be obtained by the use of carefully chosen heuristics and meta-heuristics. A heuristic can be thought of as a rule of thumb. It is a program that returns a solution which is (hopefully) of good quality but there is no guarantee of optimality. Many different heuristic methods are available, and selecting the best one (or even a combination of heuristics) is often carried out by a human expert drawing upon years of experience. However, there is generally a lack of a deep understanding as to why and when they work, with the result that significant expensive expertise and time-consuming experimentation is often required to put them into practice. The aim of this research cluster is to strengthen the theoretical understanding of how heuristics work so as to reduce the need for trial and error. Expensive mistakes (in terms of both time and resources) can be avoided and engineering efforts can be directed in more fruitful directions. Research is currently progressing towards developing a deeper understanding of the relationships between the choices of heuristics and the underlying structures of problem instances. In particular, many problems exhibit threshold behaviours in which their properties can change rapidly as problem features are changed. Cutting-edge novel research, into what we term Towards the understanding of how a heuristic performs in problem solving Parametric Parameter Tuning, is investigating the mathematical properties of such thresholds in speeding up the process of matching algorithms and control parameters to the problem instances. As another example, recent work has built Markov chain models of a state-of-the-art algorithm in order to develop a deeper understanding of why it performs so well, with a view to improving performance even further. Systems to Build Systems Building an effective decision support system can often be a rather overwhelming and expensive task. There are not many tools available, the experience of an expert is often needed and, even for an expert, there is usually a time-consuming phase of trial and error. These difficulties often mean that only large organisations have the resources to develop or purchase such systems and benefit from the potential efficiency savings. This often means that computational techniques are effectively unavailable to small and medium sized enterprises even though they form a large part of the national economy. The aim of this theme is to develop the theoretical understanding required to underpin the construction of tools and components to allow decision support systems to be built automatically and to enable them to adapt quickly to changing circumstances. The idea is to effectively capture much of the role that normally requires a human optimisation or computational search expert. Work on this challenging goal, which is being addressed in close cooperation with the heuristics understanding theme, is developing the mathematical and theoretical understanding of how to build general-purpose intelligent systems which are capable of supporting the faster and cheaper construction of new decision support systems for Small and Medium Enterprises and others. www.asap.cs.nott.ac.uk 5

Next Generation Decision Support Automating the heuristic design process Ender Ozcan and Graham Kendall visited Turkey, presenting a series of invited talks on Hyper-heuristics and the Hyflex framework for the Cross-domain Heuristic Search Challenge (CHeSc ) at the Istanbul Technical University. The talks also present the LANCS initiative and the Next Generation Decision Support: Automating the Heuristic Design Process research project. This project represents a 2.6M investment from EPSRC. The project research team is working closely with colleagues on the Systems to Build Systems cluster of the LANCS Initiative (see the previous page). Indeed this project represents the applied direction of this key strategic theme whilst the LANCS Initiative provides the theoretical direction. By working closely together, we can answer that the theory is informed by the practice and vice versa. Heuristic search methods have been successful in solving difficult real-world optimisation problems. Diverse methodologies have been proposed in Computer Science, Artificial Intelligence, and Operational Research, ranging from bio-inspired approaches to the randomisation of complete methods. However, successful heuristics need to be crafted anew for each new problem, or even just a new instance of the same problem. The goal of this project is to reduce the role of the human expert in designing effective search Two-dimensional and three-dimensional solutions obtained by an evolved packing heuristic. 6 ASAP Automated Scheduling, Optimisation and Planning Research Group

algorithms. Using machine learning or meta-level search, we have proposed methodologies which can adapt to different environments without manually having to customise the search for each particular problem domain. Successful heuristics need to be crafted anew for each new problem, or even just a new instance of the same problem. We have identified two approaches in addressing this challenge: heuristic selection, and heuristic generation. In heuristic selection, the idea is to automatically combine fixed pre-defined heuristics or neighbourhood structures to solve the problem at hand; whereas in heuristic generation the idea is to automatically create new heuristics (or heuristic components). ASAP has developed these two lines of research. An example of heuristic generation is the evolution using genetic programming of flexible packing heuristics that can generalise from one-dimensional to three-dimensional problems. Our heuristic selection research, which has been going on for about ten years, has recently seen the release of HyFlex (Hyper-heuristics Flexible framework), a Java object oriented framework for the implementation and comparison of different iterative general-purpose heuristic search algorithms (also called hyper-heuristics). The framework appeals to modularity and is inspired by the notion of a domain barrier between the low-level heuristics and the hyper-heuristic. It provides a software interface between the hyper-heuristic and the problem domain layers, thus enabling a clearly defined separation, and communication protocol between the domain specific and the domain independent algorithm components. HyFlex has led to the international challenge, the first Crossdomain Heuristic Search Challenge (CHeSC 2011), which has already gathered the attention of recognised researchers in the area of adaptive search heuristics. Problem Domains (problem) Search heuristics HyFlex HyFlex appeals to the modular design of search heuristics, and the idea of a controlled separation between the problem-specific and the general-purpose algorithm components. These components are reusable and interchangeable through the HyFlex interface www.asap.cs.nott.ac.uk 7

The Cross-domain Heuristic Search Challenge: An International Research Competition The Cross-domain Heuristic Search Challenge differed from other competitions in search and optimisation, as it aimed to measure performance over several problem domains rather than just one. We have been developing a software framework featuring a common software interface (HyFlex) for dealing with different combinatorial optimisation problems. HyFlex provides the algorithm components that are problem specific. In this way, we simultaneously liberate algorithm designers from needing to know the details of the problem domains; and prevent them from incorporating additional problem specific information in their algorithms. Efforts can instead be focused on designing high-level strategies to intelligently combine the provided problem-specific algorithmic components. The competition was organised and run by the ASAP group; with contributions from Queen s University, Belfast, UK; Cardiff University, UK; and the Ecole Polytechnique, Montreal,Canada. It was financially supported by the PATAT conference series, Aptia Solutions Ltd, EventMap Ltd and Staff Roster Solutions Ltd (see Spinout Companies section). Mustafa Mısır, a PhD student from University KaHo Sint-Lieven, Belgium with his adaptive hyperheuristic approach won the competition. MAX-SAT Flow Shop SAT Instance 1: HH1-34 HH2-23 HH3-27 HH4-10 HH5-30 Personnel Scheduling Bin Packing Hidden Domain The challenge evaluated the performance of the competing algorithms, not only across several problem instances, but also across several domains including the Travelling Salesman Problem and Vehicle Routing Problem domains. The overall scores for the top 3 algorithms Algorithm Name Score Author/Team Affiliation AdapHH 181 Mustafa Mısır University KaHo Sint-Lieven, Belgium VNS-TW 134 Ping-Che Hsiao National Taiwan University, Taiwan ML 131.5 Mathieu Larose Université de Montréa,Canada 8 ASAP Automated Scheduling, Optimisation and Planning Research Group

Educational Timetabling Educational timetabling requires the efficient allocation of events to resources whilst respecting a wide range of constraints and preferences arising from personal, institutional, governmental requests, rules and regulations. Timetabling remains a research challenge for both researchers and practitioners due to its difficulty and complexity. ASAP has been at the leading position of developing advanced algorithms and search methodologies, in addition to intelligent decision support systems in timetabling for over 15 years. Research issues and topics of particular interest to ASAP include the following: The modelling of educational timetabling problems with real world complexities and constraints The development of advanced decision support systems, supported by intelligent computational search methodologies, including heuristics, meta-heuristics, hyper-heuristics and their hybridisations The investigation and development of advanced algorithms, including meta-heuristics and hyper-heuristics in order to underpin the next generation of general and adaptive timetabling algorithms The integration of exact methods, such as integer linear programming and constraint programming, with meta-heuristics for solving large and highly constrained timetabling problems ASAP has been co-organising the conference series on the Practice and Theory of Automated Timetabling (PATAT) since 1995. The biennial PATAT conferences have been a forum for both researchers and practitioners to exchange ideas about real world timetabling and advanced decision support solutions. ASAP also co-organised the second International Timetabling Competition 2007, held in collaboration with Queen s University Belfast, Cardiff University, Edinburgh Napier University and the University of Udine. Successful approaches on both course and exam timetabling tracks from researchers around the world have been published at the PATAT2008 conference. In addition, ASAP plays a leading role in the Association of European Operational Research Societies (EURO) Working Group on Automated Timetabling (WATT), which was established in 1996. Workshops organised in alternating years within the EURO and IFORS conferences have attracted researchers and practitioners in timetabling to exchange their ideas and opinions. In addition to organising international events, EventMAP Ltd has been spun out from Queen s University Belfast and the University of Nottingham to provide automated solutions to timetabling problems. www.asap.cs.nott.ac.uk 9

Sports Timetabling Sports timetabling underpins a wide variety of scheduling problems, from high profile televised events to local amateur and children s leagues. The importance of high quality scheduling is sometimes overlooked until the effects of poor scheduling become apparent. For example, a press report from 2005 said, Football supporters and motoring organisations have called for changes in the scheduling of fixtures [over the Christmas holiday period] to prevent supporters from having to drive home from matches well into the early hours of the morning The Times (Sport, Football), 30th December 2005, page 68 In fact, the Football Association already attempt to minimise the distances that have to be travelled by football supporters over the holiday period. However, ASAP has started preliminary work on developing methodologies to address these issues. Indeed, we have had contact with London Metropolitan police to establish how policing constraints influence the real world specification of the problem. We are also working with a local company (League Republic) who provides amateur leagues with a service to schedule their fixtures through a web interface. This type of timetabling raises many challenges such as ground sharing and constraints on parents who have to transport their children to the various locations. Football supporters and motoring organisations have called for changes in the scheduling of fixtures (over the Christmas holiday period) to prevent supporters from having to drive home from matches well into the early hours of the morning. The Times (Sport, Football), 30th December 2005, page 68

Cutting and Packing Aptia VMach Virtual Cutting Machine for Simulation and Synchronisation AptiaNest Automated Nesting and CNC Generation MyNesting.com - Pay-as-you-go Automatic Nesting Cutting and packing impacts many different industries and is primarily concerned with identifying the most efficient way to utilise resources, material or space. Examples include the textile industry, where clothing pieces must be cut from a roll of fabric, international logistics where products are arranged in containers for shipping, and the optimisation of print layout where images are arranged before printing on a substrate. For many industries, even a small reduction in material requirements can give significant accumulated savings over time as the job is cut again and again. However, better use of material/space not only yields significant cost savings but also reduces the impact on the environment as less resources are required to meet production demand (or in the case of shipping containers, space is used more efficiently thus reducing the number of journeys required). ASAP has conducted research into cutting and packing problems for over fifteen years and has published many of the best performing heuristic, meta-heuristic and hyper-heuristic algorithms for both 2-dimensional and 3-dimensional problems over that period. Our published approaches obtain many of the best-known solutions for a number of internationally recognised benchmark problems and are widely cited within the literature. In light of ASAP s success in this field, Aptia Solutions (a spin-out company) was formed to further develop these approaches and to explore commercialisation opportunities. Aptia has developed a number of products, each targeting a different industry or application. Aptia has also developed a novel way of delivering its software as a pay-as-you-go service to give access to individuals and small businesses who, traditionally, have not been able to afford the large upfront cost associated with this kind of software. Currently, Aptia has many customers using its products and services including a number of high profile clients in construction, print and graphics, aerospace and Formula One racing. www.asap.cs.nott.ac.uk 11

Improving Airport and Airline Operations A view from the control tower at the Zurich airport. The modern air transportation system is a complex environment, where many different optimisation and search problems have to be solved every day. The ASAP research group have been working with airports to understand their operations and to consider where optimisation and increased automation of planning could potentially help to improve overall system performance. Meanwhile, we have simultaneously been working with airlines, seeking to increase the understanding of the causes of and propagation of delays, with an aim to being able to produce more robust flight schedules. In 2009, London Heathrow was the busiest airport in Europe and the second busiest in the world. It had more international passengers flowing through it each year than any other airport, despite having only two runways in daily use. In contrast, Paris-Charles de Gaulle has four runways. The limited number of runways means that obtaining a high runway utilisation is extremely important if delays are to be kept low and the take-off sequence has a huge effect upon the runway throughput. Our work at Heathrow has been funded by EPSRC and NATS (formerly National Air Traffic Services) Ltd, through the Smith Institute for Industrial Mathematics. We 12 ASAP Automated Scheduling, Optimisation and Planning Research Group

have considered the problem of providing realistic decision support to the controllers who sequence the take-offs from Heathrow. By harnessing the power and flexibility of modern computational search techniques, ASAP were able to build an algorithm which could make the decisions to underpin such a decision support system for the runway controllers, and to do so quickly enough that it could respond immediately to ongoing situational changes (finding answers to new problems within a second). Despite the complexity of the problem, it is currently solved manually by a runway controller in the control tower at Heathrow. Although the NATS controllers perform excellently (simulations indicate that delays would be over four times as long without the re-sequencing performed by the controllers), with up to one take-off a minute, there is insufficient time for controllers to consider all possible good take-off sequences and results predicted considerable benefits from providing the controllers with decision support to consider more aircraft and to consider them sooner. A second research project for Heathrow, again funded by NATS and EPSRC, is considering the problem of predicting the take-off sequence while aircraft are still at the stands/gates. By predicting the delay that an aircraft will have, it is then possible to absorb some of this delay at the stands rather than the runway, starting the engines later, saving fuel with commensurate environmental and economic benefits. NATS are currently integrating the system into a larger BAA system at Heathrow. ASAP has also worked closely with Air-France-KLM to investigate new approaches to build more robust schedules. The approach implemented minor changes to existing schedules, aiming to improve robustness and reduce passenger delays. A more robust schedule is one that is less sensitive to disruptions on the day of operation, offers increased flexibility to recover from disruptions, and prevents delay propagation through increased schedule stability. The approach developed by ASAP facilitates the investigation of mutual interaction between multiple robustness characteristics of a schedule and the quantification of their simultaneous influence on the schedule s operational performance. This research has contributed to fundamental new insights in the robustness of airline schedules, and a better understanding thereof, and underpins the development of future models for robust airline scheduling. The fundamental contribution of this research project was internationally recognised: it was awarded the best technical innovation at the Airline Operations Meeting of the Airline Group of the International Federation of Operational Research Societies, Denver, Colorado, 2007 and it received second place in the Anna Valicek Competition for innovative Airline Research (http://www.agifors.org/award_home.jsp). Other ongoing ASAP projects (supported by EPSRC and Zurich and Manchester airports) are considering ways to reduce the environmental impact of other airport operations, including the movement of aircraft around the airport, the allocation of stands to aircraft and the integration of the different problems in order to get better overall results. Each of these problems is a complex on its own but the combined problem is of a completely different magnitude of complexity. Nevertheless, the experience on such problems within ASAP is enabling the development of state of the art solution methods for these problems. Meanwhile, other research (supported by EPSRC and NATS) is considering the improved utilisation airport resources, to improve departure time predictability, and the optimisation of arrival operations, improving arrival time predictions and potentially helping to reduce delays for arriving aircraft while maintaining safety. The approach developed by ASAP facilitates the investigation of mutual interaction between multiple robustness characteristics of a schedule and the quantification of their simultaneous influence on the schedule s operational performance. www.asap.cs.nott.ac.uk 13

Personnel Rostering and Healthcare Personnel Rostering Staff rostering problems are found in a wide variety of environments. Some of the most complex and challenging problems arise in hospitals and healthcare centres, for example nurse and physician rostering. The benefits of automating the rostering process in these situations include reducing the planner s workload and associated costs and being able to create higher quality and more flexible schedules. This has become more important recently in order to retain nurses and to attract more people into the profession. Better quality rosters also reduce fatigue and stress due to overwork and poor scheduling and help to maximise the use of leisure time by satisfying more requests. A more contented workforce leads to higher productivity, increased quality of patient service and a better level of healthcare. RosterBooster Automated Nurse Rostering Over the years, ASAP have developed world leading rostering algorithms. We have been funded by EPSRC and industrial institutions. We are currently working with SINTEF in an international collaboration in healthcare scheduling which has been funded by EPSRC, the Research Council of Norway and industry. In 2010, ASAP formed the University spin-out company Staff Roster Solutions (http://www.staffrostersolutions.com) in order to develop the commercial potential of this research. Already in 2010 the company has made a promising start having attracted commercial licensees in Europe and North America. 14 ASAP Automated Scheduling, Optimisation and Planning Research Group

Radiotherapy Planning The ASAP group has been carrying out multidisciplinary research into radiotherapy planning and scheduling for several years. The research has been funded by EPSRC. We have worked in collaboration with Coventry University, Nottingham University Hospitals NHS Trust, University Hospitals Coventry and Warwickshire NHS Trust. Our partners in NHS trusts have provided us with their expertise in the domain of radiotherapy treatment planning and scheduling of radiotherapy patients and also with real-world data that we use in our analyses and experiments. In this field, we have investigated two major activities: 1. The generation of possible radiotherapy treatment plans for cancer patients: Case-based reasoning approaches to radiotherapy planning have been investigated. One of the main advantages of case-based reasoning is that it enables us to capture knowledge and experience of oncologists and medical physicists in radiotherapy planning. We investigate different issues that arise in the treatment of two cancer sites: (a) prostate cancer, (2) brain tumour and head and neck cancer. The main issue in prostate cancer treatment is the determination of radiation doses that are to be administered in two phases. We have developed a system for dose recommendation. The treatment of brain, head and neck cancer addresses different issues compared to prostate cancer. The dose to be delivered is usually the same for all patients, but a variety of parameters has to be determined such as the number of beams, the angles between the beams, the wedges that are used to control the distribution of radiation. 2. The scheduling of radiotherapy patients: We have develop models and algorithms for the whole process of radiotherapy planning, which includes the scheduling of a variety of resources such as the mould room, CT scanner, simulator, linear accelerators (linacs) which deliver radiation and doctors. These models consider real-world parameters and constraints, such as different categories of patients, different pathways for different sites of cancers, required type of radiation for each patient and the required number of sessions on linacs. The developed systems have enabled us to investigate the effect of an increase in patient intake and increased number of linacs on the performance of schedule. A case-based reasoning system for prostate cancer treatment www.asap.cs.nott.ac.uk 15

Outreach The ASAP research group has maintained a very successful outreach strategy, allowing us to connect our multi-disciplinary research work to the efforts of other researchers, academic institutions and industry. Prof George Steiner making a seminar presentation Commercialisation and Knowledge Transfer. ASAP has been very successful in applying our research to tackle real-world problems in industry. In addition to many of our projects having industrial partners, our research is commercialised and transferred through spin out companies and knowledge transfer partnerships (KTP). We also apply our expertise to real-world problems through KTP projects, which are partnerships between businesses and academic institutions. ASAP is involved in two KTP projects each with a 2-year duration. One KTP is a partnership with Midland HR Ltd, a company that provides human Resource management software and services to a wide range of organisations. The aim of this KTP is to develop next generation rostering software using advanced scheduling techniques. The other KTP is a partnership with 3t Logistics Ltd, a company that provides logistics and transport management services to manufacturing and distribution companies. The aim of this KTP is to design, develop and implement modern heuristic algorithms for improved, adaptive carrier management and strategic scheduling. Postgraduate Training. ASAP is a member of the National Taught Course Centre in Operational Research (NATCOR) funded by EPSRC (Ref. No. EP/E502067/1). It involves six leading universities in the field of Operational Research to develop and deliver taught courses to Operational Research PhD students in the UK, aiming to deepen and broaden their studies. ASAP is responsible for delivering the residential course at the University of Nottingham entitled Heuristics and Approximation Algorithms. The course is delivered over a two year cycle; the previous ones took place in 2008 and 2010. This course features the main techniques and also practical sessions, so that participants leave with the capabilities to start implementing their own heuristics. 16 ASAP Automated Scheduling, Optimisation and Planning Research Group

Conference Organisation ASAP has established and has been successfully running two biennial international conferences: Practice and Theory of Automated Timetabling PATAT (see www.asap.cs.nott.ac.uk/patat/patat-index.shtml) started in earlier in 1995. The previous conference took place at Queen s University Belfast, Northern Ireland, in 2010. The conference serves as a forum for an international community of researchers, practitioners and vendors on all aspects of computer-aided timetable generation. Multidisciplinary International Scheduling Conference: Theory & Applications MISTA (see www.mistaconference.org) started in 2003. The conferences have taken place in Nottingham (2003), New York (2005), Paris (2007), Dublin (2009) and the following one was held in Arizona in 2011 (August 9-12). The conference usually attracts about 120 delegates including leading scheduling researchers from around the world. PATAT2010 conference dinner at the Parliament Buildings, Stormont (Photo by Jakub Mareček) The Conference of the UK Operational Research Society OR53 (see http://www.theorsociety.com/pages/ YoungOR 17 (see http://www.theorsociety.com/pages/ Conferences/OR53/OR53.aspx) ASAP chaired the OR53 Conferences/YOR17/YOR17.aspx) ASAP was involved in the conference of the UK Operational Research Society, September programme and stream-coordination of YoungOR 17, conference 6-8, 2011. This conference was held at the East Midlands of the UK Operational Research Society intended for academics Conference Centre in Nottingham. OR53 had an impressive list of and practitioners within the first 10 years of their careers in OR. thirty one parallel streams offering a wide variety of interest on The conference took place at the University of Nottingham, 5-7 many topics. April 2011. www.asap.cs.nott.ac.uk 17

Spin Out Companies Aptia Solutions (see www.aptiasolutions.com) is a software development company that spun-out from the University of Nottingham in 2004 to provide powerful yet easy to use automated nesting solutions to industries where CNC machining is an important part of the manufacturing lifecycle. In 2010/2011, Aptia added new partners to its reseller network and has secured new customers for its flagship product, AptiaNest, in construction, aerospace, and formula one racing. Several new products have also been developed to target new customer demographics: MyNesting.com a pay per use nesting service for small businesses and hobbyists, Nestimator for more accurate costing at the quotation stage for print and signage, and a projector system to aid picking (removing parts from the cutting table) for aerospace manufacturers who require greater cutting throughput. At time of writing, there are over 1400 customers worldwide using Aptia s products to maximise material utilisation and cut out waste. The powerful cutting and packing algorithms developed by ASAP researchers are at the heart of Aptia s products. EventMAP (see www.eventmap-uk.com) is a joint venture between the University of Nottingham and Queen s University Belfast. As an innovative example of fusion between research and practice, EventMAP specialises in institutional strategic resource and event management planning via handson consultancy services that generate highly flexible, user centric-solutions and a range of innovative software products. The software is based around their state-of-the-art Optime Scheduling Engine and at the heart of EventMAP s solution provision is the integration of leading edge research based scheduling techniques which have the capability of providing significant institutional cost savings through more efficient and more satisfactory use of resource. Through the development of an innovative partnering business model, staff at EventMAP has implemented solutions in Europe, New Zealand, Australia, America, Middle East, Asia and China. The company has also taken a leading role in helping to organise the second International Timetabling Competition and the eighth PATAT conference in Belfast in 2010. Staff Roster Solutions (see www.staffrostersolutions.com) is a spin-out company formed to licence, develop and support a rostering engine which uses state-of-the-art algorithms to automatically generate optimal staff rosters. Prior to the formation of the company, the algorithms and solvers at the core of the engine were researched and developed over a number of years within ASAP. As such, the company continues to maintain close links with ASAP in order to benefit from any new advances in scheduling and optimisation theory. Although the company was only recently formed in 2010, the engine is already licensed and used by organisations in Europe and North America to create optimal rosters and work schedules. 18 ASAP Automated Scheduling, Optimisation and Planning Research Group

Professional Activities EPSRC Peer Review College J. Bacardit, A. Bargiela, E. K. Burke, G. Kendall, N. Krasnogor, J.D. Landa-Silva, S. Petrovic Company Directorships E. K. Burke: Non-executive Director of EventMAP Ltd. Director of Aptia Solutions Ltd. Director of Staff Roster Solutions Ltd. G. Kendall: Non-executive Director of EventMAP Ltd. Director of Aptia Solutions Ltd. Director of MyRIAD Solutions Fellowships E. K. Burke: Fellow of the British Computer Society Fellow of the Operational Research Society G. Kendall: Fellow of the Operational Research Society S. Petrovic: Fellow of the Institute of Mathematics and its Applications National and International Committee Memberships A. Bargiela: President of the European Council for Modelling and Simulation (Management Board Member) E. K. Burke: Advisory Board of the EPSRC IDEAS Factory Network on Productivity Advisory Board of the EPSRC SEBASE (Software Engineering By Automated SEarch) Initiative Executive Committee of the EPSRC National Training Centre for Operational Research International Advisory Board of the BBSRC/EPSRC Centre for Plant Integrative Biology Scientific Steering Committee of the Isaac Newton Institute for Mathematical Sciences (nominated by EPSRC) Scientific Committee of the Smith Institute for Industrial Mathematics and System Engineering European Science Foundation (ESF) Pool of Reviewers UK Computing Research Committee (UKCRC) General Council of the OR Society Education and Research Committee of the OR Society Management Board of the EPSRC LANCS Initiative (Chairman) Executive Committee of the EPSRC LANCS Initiative (Chairman) Advisory Board of the First Cross-domain Heuristic Search Challenge www.asap.cs.nott.ac.uk 19

Professional Activities S.Y. Chong: Awards Subcommittee of the IEEE Computational Intelligence Society Outstanding PhD Dissertation, 2009-2011 M. Hyde: Organising Committee of the First Cross-domain Heuristic Search Challenge (Co-chair) G. Kendall: Advisory Board of the First Cross-domain Heuristic Search Challenge Steering Commitee of the International Conference on Machine Learning and Applications, 2010 Steering Commitee of the International Conference on Machine Learning and Applications, 2009 G. Ochoa: Management Board of the Next Generation Decision Support: Automating the Heuristic Design Process Organising Committee of the First Cross-domain Heuristic Search Challenge (Co-chair) E. Özcan: Executive Committee of the EPSRC LANCS Initiative Advisory Board of the First Cross-domain Heuristic Search Challenge Organising Commitee of the ROADEF/EURO Challenge, 2010 A.J. Parkes: Executive Committee of the EPSRC LANCS initiative Advisory Board of the First Cross-domain Heuristic Search Challenge S. Petrovic: Executive Committee of the EPSRC LANCS initiative EURO (European Association of Operational Research Societies) Working group on Automated Timetabling WATT (Coordinator). Executive Committee of the EPSRC National Training Centre for Operational Research (NATCOR) Advisory Board of the First Cross-domain Heuristic Search Challenge R. Qu: International Advisory Board of the Third Conference on Data Mining and Optimization (DMO 09), Universiti Kebangsaan, Malaysia, 2009 Task Committee on Intelligent Systems Applications at IEEE Computational Intelligence Society (Member) Task Force on Evolutionary Scheduling and Timetabling of Evolutionary Computation Technical Committee (ECTC), IEEE Computational Intelligence Society (Chair) Journal Editorships J. Bacardit: Editorial Board of the International Journal of Applied Metaheuristic Computing Guest Co-editor of the special issue of the Memetic Computing journal on Metaheuristics for Large-Scale Data Mining, 2010 A. Bargiela: Associate Editor of IEEE Transactions on Systems, Man and Cybernetics, Part A Editor-in-chief of Modelling and Simulation in Engineering, Hindawi Press Associate Editor of Editorial Board of Information Sciences Editorial Board of the International Journal of Intelligent Decision Technologies (Member) Editorial Board of Journal of Advanced Computational Intelligence and Intelligent Informatics (Member) Editorial Board of the International Journal of Knowledge Engineering Systems (Member) Editorial Board of the International Journal of Simulation: Systems, Science & Technology (Member) E. K. Burke: Editor-in-Chief of the Journal of Scheduling Area Editor (for Combinatorial Optimisation) of the Journal of Heuristics Associate Editor of the INFORMS Journal on Computing Associate Editor of the IEEE Transactions on Evolutionary Computation Editorial Board of Memetic Computing (Member) Guest Co-editor of a special issue of the Journal of the Operational Research Society on Systems to Build Systems, 2010 20 ASAP Automated Scheduling, Optimisation and Planning Research Group

S.Y. Chong: Associate Editor of the IEEE Transactions on Computational Intelligence and AI in Games. G. Kendall: Associate Editor of the Journal of the Operational Research Society Associate Editor of IEEE Transactions on Evolutionary Computation Associate Editor of IEEE Transactions on Computational Intelligence and Artificial Intelligence in Games Associate Editor of Computational Intelligence Associate Editor of the International Journal of Systems Science Associate Editor of Intelligent Systems in Accounting Finance and Management Associate Editor of INFOR: Information Systems and Operational Research Associate Editor of Cognitive Neurodynamics Associate Editor of International Journal of Intelligent Computing and Cybernetics N. Krasnogor: Founding Editor-in-Chief (technical) for the Memetic Computing Journal, Springer Associate Editor of Evolutionary Computation, MIT Editor for Current Opinion in Biotechnology, Elsevier D. Landa-Silva: Editorial Board for the Memetic Computing Journal (Member) P.K. Lehre: Editorial Board for the Evolutionary Computation, MIT Press Guest Co-editor of the special issue of the Theoretical Computer Science on Theoretical Foundations of Evolutionary Computation, 2011 J. Li: Editorial Board for the Wireless Sensor Network (Member) G. Ochoa: Associate Editor of Evolutionary Computation, MIT Press Guest Co-editor of the special issue of the Evolutionary Computation Journal on Automated Design and Assessment of Heuristic Search Methods, 2011 Guest Co-editor of the special issue of the Journal of Heuristics on Hyper-heuristics in Search and Optimisation, 2010 E Özcan: Associate Editor of the International Journal of Applied Metaheuristic Computing Guest Co-editor of a special issue of the Journal of the Operational Research Society on Systems to Build Systems, 2011 Guest Co-editor of the special issue of the Journal of Scheduling on Maintenance Scheduling: Theory and Applications, 2011 Guest Co-editor of the special issue of the Journal of Heuristics on Hyper-heuristics in Search and Optimisation, 2010 S. Petrovic: Associate Editor in the IMA Journal of Management Mathematics, Oxford University Press Editorial Board of the Yugoslav Journal of Operations Research - YUJOR (Member) R.Qu: Guest Co-editor of the special issue of the IEEE Transactions on Evolutionary Computation on Evolutionary Computation in Scheduling, 2011 Guest Co-editor of the special issue of the Journal of Scheduling on Artificial Intelligence Planning and Scheduling, 2009 www.asap.cs.nott.ac.uk 21

Professional Activities Chairing of Conferences J. Bacardit: Workshops Chair of the Genetic and Evolutionary Computation Conference (GECCO), Porland, Oregon, 2010 A. Bargiela: Chair of the European Conference on Modeling and Simulation (ECMS 2010), Kuala Lumpur, June 2010 Chair of the European Conference on Modeling and Simulation (ECMS 2009), Madrid, Spain, June 2010 E. K. Burke: Co-chair of the Programme Committee of the 8th international conference on the Practice and Theory of Automated Timetabling (PATAT 10), Belfast, August 2010 G. Kendall: Plenary Session Co-chair for the IEEE Congress on Evolutionary Computation (CEC), New Orleans, 2011. Co-chair of the 3rd Conference on Data Mining and Optimization (DMO), Bangi, Malaysia, 2011. Co-chair of the 5th Multidisciplinary International Conference on Scheduling : Theory and Applications (MISTA) conference, Phoenix, Arizona, USA, 2011. Co-chair of the 4th Multidisciplinary International Conference on Scheduling : Theory and Applications (MISTA) conference, Dublin, Ireland, 2009 N. Krasnogor: Co-chair of the 2nd European Conference on Synthetic Biology, Sant Feliu de Guixols (Costa Brava), Spain, 2009. E. Özcan: Co-chair of the IEEE Symposium on Computational Intelligence in Scheduling (CI-Sched 2011), Paris, France, 2011. Joint programme scheduler and stream co-ordinator for the YoungOR conference, Nottingham, UK, 2011. A. J. Parkes: Joint programme scheduler and stream co-ordinator for the YoungOR conference, Nottingham, UK, 2011. S. Petrovic: Chair of the UK Operational Research Society (OR53) conference, Nottingham, UK, 2011. R. Qu: Co-chair of the IEEE Symposium on Computational Intelligence in Scheduling (CI-Sched 2011), Paris, France, 2011. Co-chair of the IEEE Symposium on Computatal Intelligence in Scheduling (CI-Sched 2009), Nashville, TN, USA, 2009 Conference Programme Committee Memberships (2009 2011) J. Bacardit:...................................................................................................................................................................18 (2009-10) R. Bai:........................................................................................................................................................................................... 5 A. Bargiela:...................................................................................................................................................................12 (2009-10) E. K. Burke:..................................................................................................................................................................14 (2009-10) S. Y. Chong:................................................................................................................................................................................... 6 M. Hyde:....................................................................................................................................................................................... 8 G. Kendall:................................................................................................................................................................................... 50 N. Krasnogor:................................................................................................................................................................23 (2009-10) D. Landa-Silva:............................................................................................................................................................................. 30 P.K. Lehre:..................................................................................................................................................................................... 9 J. Li:............................................................................................................................................................................................. 5 G. Ochoa:...................................................................................................................................................................................... 8 E. Özcan:..................................................................................................................................................................................... 23 A. J. Parkes:................................................................................................................................................................................... 4 S. Petrovic:.................................................................................................................................................................................. 15 R. Qu:......................................................................................................................................................................................... 26 22 ASAP Automated Scheduling, Optimisation and Planning Research Group

Honours and Awards J. Bacardit: Best paper award, M. Franco, N. Krasnogor and J. Bacardit. Speeding Up the Evaluation of Evolutionary Learning Systems using GPGPUs. In Proceedings of the 12th Annual Conference on Genetic and Evolutionary Computation (GECCO2010), 1039-1046, 2010. A. Bargiela: Medal of Merit for his achievements in Computational Intelligence and academic collaboration, Silesian University of Technology, Poland, 2009. Titular Professor, conferred by the President of Poland, 2009. Best Presentation Award, International Workshop on Advanced Computer Informatics (IWACIII2009), Tokyo, Japan, 2009. Y. Bykov: Winner of the International Optimisation Competition which was arranged by SolveIT Software Pty Ltd., 2011. His approach, namely Late Acceptance Hill-Climbing algorithm solved the constrained version of 2,600 x 2,600 magic square within a minute. S.Y. Chong: Outstanding Paper Award, 2011, IEEE Transactions on Evolutionary Computation. S. Y. Chong, P. Tino, and X. Yao. Measuring Generalization Performance in Co-evolutionary Learning. IEEE Transactions on Evolutionary Computation, vol. 12, no. 4, 479-505, 2008. Winner of Ms Pac-Man vs Ghosts Competition, H. B.Low and S.Y. Chong, Pac-Man Controllers category, IEEE Congress on Evolutionary Computation, New Orleans, USA, 2011. Best paper award, C. W. Kheng, M. H. Lim, and S. Y. Chong. A Study on Lamarckian and Baldwinian Learning on Noisy and Noiseless Landscapes. In Proceedings of the 24th European Conference on Modelling and Simulation (ECMS 2010), 323-329, 2010. IEEE Computational Intelligence Society Outstanding PhD Dissertation Award, S. Y. Chong. Generalization and Diversity in Coevolutionary Learning, PhD thesis, School of Computer Science, University of Birmingham, UK, 2009. N. Krasnogor: Best paper award, M. Franco, N. Krasnogor and J. Bacardit. Speeding Up the Evaluation of Evolutionary Learning Systems using GPGPUs. In Proceedings of the 12th Annual Conference on Genetic and Evolutionary Computation (GECCO2010), 1039-1046, 2010. Gold medal prize at the 2010 HUMIES, 2010. The 2010 ACM s Special Interest Group on Evolutionary Computation Impact Award for the most highly cited paper of those published in a GECCO proceeding 10 years earlier. P.K. Lehre: Best paper award, P.K. Lehre and C. Witt, Black Box Search by Unbiased Variation. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2010), 1441-1449, 2010. Best paper award, P. Rohlfshagen, P. K. Lehre and X. Yao. Dynamic Evolutionary Optimisation: An Analysis of Frequency and Magnitude of Change. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2009), 1713-1720, 2009. E. Özcan: Best paper award, E. Özcan, and A. J. Parkes. Policy Matrix Evolution for Generation of Heuristics, Proceedings of the 13th Annual Conference on Genetic and Evolutionary Computation (GECCO 11), Natalio Krasnogor (Ed.), 2011-2018, 2011. A. J. Parkes: Best paper award, E. Özcan, and A. J. Parkes. Policy Matrix Evolution for Generation of Heuristics, Proceedings of the 13th Annual Conference on Genetic and Evolutionary Computation (GECCO 11), Natalio Krasnogor (Ed.), 2011-2018, 2011. www.asap.cs.nott.ac.uk 23

Publications (2009-2011) Books 2010 J. Bacardit, W. Browne, J. Drugowitsch, E. Bernado-Mansilla, and M.V. Butz. Learning Classifier Systems. 11th International Workshop, IWLCS-2008, Atlanta, GA, USA, July 13, 2008 and 12th International Workshop, IWLCS-2009, Montreal, QC, Canada, July 9, 2009. Revised Selected Papers, Lecture Notes in Artificial Intelligence 6471. A. Bargiela, S.A. Ali, D. Crowley, and E. Kerckhoffs. Simulation meets global challenges. ECMS Press, 2010. C. Cruz, J. Gonzalez, N. Krasnogor, and G. Terraza. Nature Inspired Cooperative Strategies for Optimization (NICSO 2010). Volume 284, Springer, 2010. N. Krasnogor, B. Melian-Batista, J.A. Moreno-Perez, J.M. Moreno-Vega, and D. Pelta. Nature Inspired Cooperative Strategies for Optimization (NICSO 2008). Volume 236, Springer, 2009. 2009 A. Bargiela and W. Pedrycz. Human-centric information processing through granular modelling. Springer, 2009. Book Chapters 2011 S. Petrovic, D. Petrovic and E. Burke. Fuzzy logic based production scheduling/rescheduling in the presence of uncertainty. In: K. Kempf, P. Keskinocak, R. Uzsoy (eds.), Planning Production and Inventories in the Extended Enterprise, A State of the Art Handbook, vol. 2, International Series in Operation Research and Management Science 157, chapter 20, 531-562. Springer, 2011. S. Petrovic and E. Castro. Applications of Evolutionary Computation, A genetic algorithm for radiotherapy pre-treatment scheduling. In: C. Di Chio et al. (eds.), Lecture Notes in Computer Science 6625, part II, 454-463. Springer, 2011. 2010 E. K. Burke, M. Hyde, G. Kendall, G. Ochoa, E. Özcan, and J. Woodward. Handbook of Metaheuristics, A classification of hyper-heuristic approaches. International Series in Operations Research & Management Science, vol. 146, 449-468. Springer, 2010. P. Cazzaniga, M. Gheorghe, N. Krasnogor, G. Mauri, D. Pescini, and F. J. Romero-Campero. Probabilistic/stochastic models. Oxford Handbooks in Mathematics. In: G. Paun and G. Rozenberg and A. Salomaa (eds.), The Oxford Handbook of Membrane Computing, chapter 18, 2010. L.W. Lee, A. Bargiela. Statistical extraction of protein surface atoms based on a voxelisation method. In: A. Bargiela, S.A. Ali, D. Crowley, E. Kerckhoffs (eds.), Simulation Meets Global Challenges. ECMS Press, 344-349, 2010. T. Maul, A. Bargiela, L. J. Ren. A neuroalgorithmic investigation of the outer retina. In: A. Bargiela, S.A. Ali, D. Crowley, and E. Kerckhoffs (eds.), Simulation Meets Global Challenges. ECMS Press, 337-343, 2010. J. H. Obit and D. Landa-Silva. Computational study of non-linear great deluge for university course timetabling. In: V. Sgurev, M. Hadjiski and J. Kacprzyk (eds.), Studies in Computational Intelligence: Intelligent Systems - From Theory to Practice. Springer-Verlag, 309-328, 2010. G. Terrazas, D. Landa-Silva, N. Krasnogor. Discovering beneficial cooperative structures for the automatic construction of heuristics. In: J. R. Gonzalez, D. A. Pelta, C. Cruz, G. Terrazas and N. Krasnogor (eds.), Studies in Computational Intelligence: Nature Inspired Cooperative Strategies for Optimization (NICSO 2010). Springer-Verlag, 89-100, 2010. 24 ASAP Automated Scheduling, Optimisation and Planning Research Group

2009 G. Baskaran, A. Bargiela and R. Qu. Hierarchical method for nurse rostering based on granular pre-processing of constraints. In: J. Otamendi, A. Bargiela, J.L. Montes and L.M.D. Pedrera (eds.), Simulation Science and Technology: Proc. ECMS 2009. ECMS Press, 855-861, 2009. E. K. Burke, M. R. Hyde, G. Kendall, G. Ochoa, E. Ozcan, and J. R. Woodward. Exploring hyper-heuristic methodologies with genetic programming. Computational Intelligence: Collaboration, Fusion and Emergence, Springer-Verlag, 177-201, 2009. J. P. Castro, D. Landa-Silva and J. A. Moreno. Exploring feasible and infeasible regions in the vehicle routing problem with time windows using a multi-objective particle swarm optimization approach. In: N. Krasnogor, B. Melin-Batista, J.A. Moreno-Prez, J.M. Moreno-Vega and D. Pelta (eds.), Studies in Computational Intelligence: Nature Inspired Cooperatives Strategies for Optimization (NICSO 2008). Springer- Verlag vol. 236, 103-114, 2009. W. K. Cheng, S. Y. Chong and A. Bargiela. Multi-resolution optimisation: Application of meta-heuristics in function re-modelling. In: J. Otamendi, A. Bargiela, J.L. Montes, and L.M.D. Pedrera (eds.), Simulation Science and Technology: Proc. ECMS 2009. ECMS Press, 834-840, 2009. N. Krasnogor. Memetic algorithms. Natural Computing. In: T. Baeck and G. Rozenberg (eds.), Handbook of Natural Computation, 2009. D. Landa-Silva, J. H. Obit. Hybrid Artificial Intelligent Systems, Evolutionary Non-linear great deluge for university course timetabling, 269-276. In: E. Corchado, X. Wu, E. Oja, Herrero, and B. Baruque (eds.), Lecture Notes in Computer Science 5572. Springer, 2009. L. W. Lee and A. Bargiela. Space-partition based identification of protein docksites. In: J. Otamendi, A. Bargiela, J.L. Montes, and L.M.D. Pedrera (eds.), Simulation Science and Technology: Proc. ECMS 2009. ECMS Press, 848-854, 2009. D. Petrovic, M. Morshed, and S. Petrovic. Artificial Intelligence in Medicine, Genetic algorithm based scheduling of radiotherapy treatments for cancer patients, 101-105. Lecture Notes in Artificial Intelligence 5651. Springer, 2009. F. J. Romero-Campero and N. Krasnogor. Mathematical Theory and Computational Practice, An approach to the engineering of cellular models based on P Systems, 430-436. Lecture Notes in Computer Science. Springer Berlin / Heidelberg, 2009. S. K. Rahim and A. Bargiela. Granular modelling of exam to slot allocation. In: J. Otamendi, A. Bargiela, J.L. Montes, and L.M.D. Pedrera (eds.), Simulation Science and Technology: Proc. ECMS 2009. ECMS Press, 861-866, 2009. W. Wang and A. Bargiela. Multi-resolution modelling of topic relationships in semantic space. In: J. Otamendi, A. Bargiela, J.L. Montes, and L.M.D. Pedrera (eds.), Simulation Science and Technology: Proc. ECMS 2009. ECMS Press, 813-818, 2009. PhD Theses 2011 P. Rocha. Novel Approaches to Radiotherapy Treatment Scheduling, PhD Dissertation, University of Nottingham, May 2011. N. Mishra. A Novel Case-Based Reasoning Approach to Radiotherapy Dose Planning, PhD Dissertation, University of Nottingham, December 2011. Ying Xu. Metaheuristic Approaches for QoS Multicast Routing Problems. PhD dissertation, University of Nottingham, January 2011. www.asap.cs.nott.ac.uk 25

2010 G. de Maere. Multi-Objective Approaches to Investigate Airline Schedule Robustness, PhD Dissertation, University of Nottingham, January 2010. K. Xiao. Brain Magnetic Resonance Image Tumour Segmentation with Lateral Ventricular Deformation, PhD Dissertation, The University of Nottingham Malaysia Campus, February 2010. 2009 J. Baxter. Collaborative Decision Making in Uncertain Environments, PhD Dissertation, the University of Nottingham, April 2009. M. Hyde. Genetic Programming Hyper-Heuristic Approach to Automated Packing, PhD Dissertation, the University of Nottingham, December 2009. W. Wei. Semantic Search: Bringing Semantic Web Technologies to Information Retrieval, PhD Dissertation, The University of Nottingham Malaysia Campus, July 2009. Journal Papers 2011 S. Allen, E. Burke, and G. Kendall. A hybrid placement strategy for the three-dimensional strip packing problem. European Journal of Operational Research, 209(3):219-227, 2011. J. Atkin, E.K. Burke and J. Greenwood. A comparison of two methods for reducing take-off delay at London Heathrow airport. Journal of Scheduling, (14)5: 409-421, 2011. P. Brucker, R. Qu, and E. K. Burke. Personnel scheduling: Models and complexity. European Journal of Operational Research, 210(3):467-473, 2011. E. Castro and S. Petrovic. Combined mathematical programming and heuristics for a radiotherapy pre-treatment scheduling problem. Journal of Scheduling, 2011. F. Daolio, M. Tomassini, S.Verel and G. Ochoa. Communities of minima in local optima networks of combinatorial spaces. Physica A: Statistical Mechanics and its Applications, (390)9: 1684-1694, 2011. H. Li and D. Landa-Silva. An adaptive evolutionary multi-objective approach based on simulated annealing. Evolutionary computation, 19(4), 2011. J. Li., E. Burke, T. Curtois, S. Petrovic and R. Qu. The falling tide algorithm: A new multi-objective approach for complex workforce scheduling. Omega, 283-293, 2011. J. Li, A. J. Parkes, and E. K. Burke. Evolutionary squeaky wheel optimization: A new analysis framework. Evolutionary Computation, 19(3):405-428, 2011. D. Petrovic, M. Morshed, and S. Petrovic. Multi-objective genetic algorithms for scheduling of radiotherapy treatments for categorised cancer patients. Expert Systems with Applications, 38(6):6994-7002, 2011. S. Petrovic, N. Mishra, and S. Sundar. A novel case based reasoning approach to radiotherapy planning. Expert Systems with Applications, 38(9):10759-10769, 2011. 26 ASAP Automated Scheduling, Optimisation and Planning Research Group

B. Ryan, R. Qu, A. Schock, and T. Parry. Integrating human factors and operational research in a multidisciplinary investigation of road maintenance. Ergonomics, 54(5):436-452, 2011. H. Xing and R. Qu. A population based incremental learning for network coding resources minimization. IEEE Communication Letters, 99:1-3, 2011. J. A. Rodriguez-Vazquez and G. Ochoa. On the automatic discovery of variants of the NEH procedure for flow shop scheduling using genetic programming. Journal of the Operational Research Society, 62(2): 381-396, 2011. S.Verel and G. Ochoa and M. Tomassini. Local optima networks of NK landscapes with neutrality. IEEE Transactions on Evolutionary Computation, (15)6: 783-797, 2011. J. A. Rodriguez-Vazquez and G. Ochoa. On the automatic discovery of variants of the NEH procedure for flow shop scheduling using genetic programming. Journal of the Operational Research Society, 62(2): 381-396, 2011. S.Verel and G. Ochoa and M. Tomassini. Local optima networks of NK landscapes with neutrality. IEEE Transactions on Evolutionary Computation, (15)6: 783-797, 2011. 2010 R. Andriansyah, T. van Woensel, F. R. B. Cruz, and L. Duczmal. Performance optimization of open zero-buffer multi-server queueing networks. Computers & Operations Research, 37(8):1472-1487, 2010. R. Bai, E. K. Burke, G. Kendall, J. Li, and B. McCollum. A hybrid evolutionary approach to the nurse rostering problem. IEEE Transactions on Evolutionary Computation,14(4): 580-590, 2010. J.M. Binner, P. Tino, J. Tepper, R. Anderson, B. Jones, and G. Kendall. Does money matter in inflation forecasting? Physica A: Statistical Mechanics and its Applications, 389(21): 4793-4808, 2010. P. Brucker, E. K. Burke, T. Curtois, R. Qu, and G. Vanden Berghe. A shift sequence based approach for nurse scheduling and a new benchmark dataset. Journal of Heuristics, 16(4): 559-573, 2010. E. K. Burke, P. De Causmaecker, G. De Maere, J. Mulder, M. Paelinck, and G. Vanden Berghe. A multi-objective approach for robust airline scheduling. Computers & Operations Research, 37:822-832, 2010. E. K. Burke, T. Curtois, R. Qu, and G. Vanden Berghe. A scatter search for the nurse rostering problem. Journal of Operational Research Society, 61: 1667-1679, 2010. E. K. Burke, A. Eckersley, B. McCollum, S. Petrovic, and R.Qu. Hybrid variable neighbourhood approaches to university exam timetabling. European Journal of Operational Research, 206: 46-53, 2010 E. K. Burke, R. S. R. Hellier, G. Kendall, and G. Whitwell. Irregular packing using the line and arc no-fit polygon. Operations Research, 58(4), part 1: 948-970, 2010. E. K. Burke, M. Hyde, G. Kendall, and J. Woodward. A Genetic Programming hyper-heuristic approach for evolving 2-d strip packing heuristics. IEEE Transactions on Evolutionary Computation, 14(6):942-958, 2010. www.asap.cs.nott.ac.uk 27

E. K. Burke, J. Li, and R. Qu. A hybrid model of integer programming and variable neighbourhood search for highly-constrained rostering problems. European Journal of Operational Research, 203(2): 484-493, 2010. E. K. Burke, J. Marecek, A. J. Parkes, and H. Rudová. Decomposition, reformulation, and diving in university course timetabling. Computers & Operations Research, 37(1):582-597, 2010. E. K. Burke, J. Marecek, A. J. Parkes, and H. Rudová. A supernodal formulation of vertex colouring with applications in course timetabling. Annals of Operations Research, 179(1):105-130, 2010. H. Cao, F.J. Romero-Campero, S. Heeb, M. Cámara, and N. Krasnogor. Evolving cell model for systems and synthetic biology. Systems and Sythetic Biology, 4(1):55-84, 2010. F. R. B. Cruz, P. C. Oliveira, and L. Duczmal. State-dependent stochastic mobility model in mobile communication networks. Simulation Modelling Practice and Theory, 18(3):348-365, 2010. F. R. B. Cruz, T. van Woensel, and J. MacGregor Smith. Buffer and throughput trade-offs in M/G/1/K queueing networks: A bi-criteria approach. International Journal of Production Economics, 125(2):224-234, 2010. F. R. B. Cruz, T. van Woensel, J. MacGregor Smith, and K. Lieckens. On the system optimum of traffic assignment in M/G/c/c statedependent queueing networks. European Journal of Operational Research, 201(1):183-193, 2010. G. J. Davies, G. Kendall, E. Soane, J. Li, F. Charnley, and S. J. T. Pollard. Regulators as agents : power and personality in risk regulation and a role for agent-based simulation. Journal of Risk Research, 13(8): 961-982, 2010. O. Giel, P.K. Lehre. On the Effect of populations in evolutionary multi-objective optimisation. Evolutionary Computation, 18:335-356, 2010. E. Glaab, A. Baudot, N. Krasnogor, and A. Valencia. TopoGSA: network topological gene set analysis. Bioinformatics, 26(9):1271-1272, 2010. E. Glaab, J. M. Garibaldi, and N. Krasnogor. VRMLGen: An R package for 3D data visualization on the web. Journal of Statistical Software, 36(8):1-18, 2010. M. N. M. Kahar and G. Kendall. The examination timetabling problem at Universiti Malaysia Pahang: Comparison of a constructive heuristic with an existing software solution. European Journal of Operational Research, 207(2): 557-565, 2010 G. Kendall, S. Knust, C.C. Ribeiro, and S. Urrutia. Scheduling in sports: An annotated bibliography. Computers & Operations Research, 37(1): 1-19, 2010. P.K. Lehre and X. Yao. Crossover can be constructive when computing unique input-output sequences. Soft Computing. 1-13, 2010. J. Li, E. K. Burke, and R. Qu. Integrating neural network and logistic regression to underpin hyper-heuristic search. Knowledge-Based Systems. 24(2): 322-330, 2010. J. Li and G. Kendall. Collective behaviour and kin selection in evolutionary iterated prisoners dilemma. Journal of Multiple-Valued Logic and Soft Computing, 16(6): 509-525, 2010. 28 ASAP Automated Scheduling, Optimisation and Planning Research Group

B. McCollum, P. McMullan, B. Paechter, R. Lewis, A. Schaerf, L. Di Gaspero, A. J. Parkes, R. Qu, and E. Burke. Setting the research agenda in automated timetabling: The second international timetabling competition. INFORMS Journal of Computing, 22(1): 120-130, 2010. P. Moratori., S. Petrovic, and J.A. Vázquez-Rodríguez. Integrating Rush Orders into Existent Schedules for a Complex Job Shop, Applied Intelligence, 32(2):205-215, 2010. D. Ouelhadj and S. Petrovic. A cooperative hyper-heuristic search framework. Journal of Heuristics, (16)6, 835-857, 2010. E. Özcan, M. Mısır, G. Ochoa, and E. K. Burke. A reinforcement learning-great-deluge hyper-heuristic for examination timetabling. International Journal of Applied Metaheuristic Computing, 1(1):39-59, 2010. W. Pedrycz and A. Bargiela. Fuzzy clustering with semantically distinct families of variables: Descriptive and predictive aspects. Pattern Recognition Letters, 31(13), 1952-1958, 2010. J. Smaldon, F. J. Romero-Campero, F. Fernandez Trillo, M. Gheorghe, C. Alexander, and N. Krasnogor. A computational study of liposome logic: towards cellular computing from the bottom up. Systems and Synthetic Biology, 4(3): 157-179, 2010. J. M. Smith, F. R. B. Cruz, and T. van Woensel. Topological network design of general, finite, multi-server queueing networks. European Journal of Operational Research, 201(2):427-441, 2010. R. E. Smith and M. K. Jiang and J. Bacardit and M. Stout and N. Krasnogor and J.D. Hirst. A learning classifier system with mutualinformation-based fitness. Evolutionary Intelligence, 3(1): 31-50, 2010. J. Twycross and U. Aickelin. Information fusion in the immune system. Information Fusion, 11 (Special Issue on Biologically Inspired Information Fusion):35-44, 2010. J. Twycross, L.R. Band, M. J. Bennett, J.R. King, and N. Krasnogor. Stochastic and deterministic multiscale models for systems biology: an auxin-transport case study. BMC Systems Biology, 4:34, 1-11, 2010. O. Ulker and D. Landa-Silva. A 0/1 Integer Programming model for the office space allocation problem. Electronic Notes in Discrete Mathematics, 36: 575-582, 2010. T. van Woensel, R. Andriansyah, F. R. B. Cruz, J. MacGregor Smith, and L. Kerbache. Buffer and server allocation in general multi-server queueing networks. International Transactions in Operational Research, 17(2):257-286, 2010. M. Villasana, G. Ochoa, and S. Aguilar. Modeling and optimization of combined cytostatic and cytotoxic chemotherapy. Artificial Intelligence in Medicine, vol. 50, 163-173, 2010. W. Wang, P. Barnaghi, and A. Bargiela. Probabilistic topic models for learning terminological ontologies. IEEE Transactions on Knowledge and Data Engineering, 22(7), 1028-1040, 2010. www.asap.cs.nott.ac.uk 29

P. Widera, J.Garibaldi, and N. Krasnogor. GP challenge: evolving energy function for protein structure prediction. Genetic Programming and Evolvable Machines, 11(1):61-88, 2010. K. Xiao, S.H. Ho, and A. Bargiela. Automatic brain PMRI segmentation scheme based on feature weighting factors selection. International Journal of Computational Intelligence in Bioinformatics and System Biology, 1(3), 316-331, 2010. Y. Xu and R. Qu. Solving multi-objective multicast routing problems by evolutionary multi-objective simulated annealing algorithms with variable neighborhoods. Journal of Operational Research Society, 62: 313-325, 2010. S. Yang, D. Wang, T. Chai, and G. Kendall. An improved constraint satisfaction adaptive neural network for job-shop scheduling. Journal of Scheduling, 13(1):17-38, 2010. 2009 E. Agafonov, A. Bargiela, E. Burke, and E. Peytchev. Mathematical justification of a heuristic for statistical correlation of real-life time series. European Journal of Operational Research, 198, 275-286, 2009. U. Aickelin, E. K. Burke, and J. Li. An evolutionary squeaky wheel optimisation approach to personnel scheduling. IEEE Transactions on Evolutionary Computation, 13(2):433-443, 2009. J. Alcalá-Fdez, L. Sánchez, S. García, M. J. del Jesus, S. Ventura, J.M Garrell, J. Otera, C. Romero, J. Bacardit, V.M. Rivas, and J.C. Fernández. Keel: A software tool to assess evolutionary algorithms for data mining problems. Soft Computing - A Fusion of Foundations, Methodologies and Applications, 13(3):307-318, 2009. Ö. B. Aşık and E. Özcan. Bidirectional best-fit approach for orthogonal rectangular strip packing. Annals of Operations Research, 172:405-27, 2009. J.A.D. Atkin, E. K. Burke, J.S. Greenwood, and D. Reeson. An examination of take-off scheduling constraints at London Heathrow airport. Public Transport, 3(1): 169-187, 2009. M. Ayob and G. Kendall. The optimisation of the single surface mount device placement machine in printed circuit board assembly: A survey. International Journal of Systems Science, 40(60): 553-569, 2009. J. Bacardit, E. K. Burke, and N. Krasnogor. Improving the scalability of rule-based evolutionary learning. Memetic Computing Journal, 1(1):55-67, 2009. J. Bacardit and N. Krasnogor. Performance and efficiency of memetic Pittsburgh learning classifier systems. Evolutionary Computation Journal, 17(3):307-342, 2009. J. Bacardit, M. Stout, J. D. Hirst, A. V., R. E. Smith, and N. Krasnogor. Automated alphabet reduction for protein datasets. BMC Bioinformatics, 10:6, 2009. C. Barteczko-Hibbert, M. Gillott, and G. Kendall. An artificial neural network for predicting domestic hot water characteristics. International Journal of Low-Carbon Technologies, 4(2):112-119, 2009. 30 ASAP Automated Scheduling, Optimisation and Planning Research Group

G. Beddoe, S. Petrovic, and J. Li. A hybrid metaheuristic case-based reasoning system for nurse rostering. Journal of Scheduling, 12(2):99-119, 2009. C. Beyrouthy, E. K. Burke, D. Landa-Silva, B. McCollum, P. McMullan, and A. J. Parkes. Towards improving the utilisation of university teaching space. Journal of the Operational Research Society, 60(1):130-143, 2009. J. M. Binner, A. M. Gazely, and G. Kendall. An evaluation of UK risky money: an artificial intelligence approach. Global Business and Economics Review, 11(1): 1-18, 2009. E. K. Burke, G. Kendall, and G. Whitwell. A simulated annealing enhancement of the best-fit heuristic for the orthogonal stock cutting problem. INFORMS Journal on Computing, 21(3):505-516, 2009. S. Y. Chong, P. Tino, and X. Yao. Relationship between generalization and diversity in co-evolutionary learning. IEEE Transactions on Computational Intelligence and AI in Games, 3(1):214-232, 2009. E. Glaab, J. M Garibaldi, and N. Krasnogor. ArrayMining: a modular web-application for microarray analysis combining ensemble and consensus methods with cross-study normalization. BMC Bioinformatics, 10(358):358, 2009. J. Li, U. Aickelin, and E. K. Burke. A component-based heuristic search method with evolutionary eliminations for hospital personnel scheduling. INFORMS Journal on Computing, 21(3): 468-479, 2009. J. Li and G. Kendall. A strategy with novel evolutionary features for the iterated prisoner s dilemma. Evolutionary Computation, 17(2):257-274, 2009. J. Li, S. Pollard, G. Kendall, E. Soane, and G. Davies. Optimising risk reduction: An expected utility approach for marginal risk reduction during regulatory decision making. Reliability Engineering & System Safety, 94(11):1729-1734, 2009. L. Li, J. Garibaldi, and N. Krasnogor. Automated self-assembly programming paradigm: The impact of network topology. International Journal of Intelligent Systems (IJIS), 24(7):793-817, 2009. Special issue on Nature Inspired Cooperative Strategies for Optimisation. D.Ouelhadj and S. Petrovic. Survey of dynamic scheduling in manufacturing systems. Journal of Scheduling, 12(4):417-431, 2009. E. Özcan and C. Başaran. A case study of memetic algorithms for constraint optimization. Soft Computing, 13(8-9):871-882, 2009. R. Qu and E. K. Burke. Hybridisations within a graph based hyper-heuristic framework for university timetabling problems. Journal of Operational Research Society, 60:1273-1285, 2009. R. Qu, E. K. Burke, B. McCollum, L.T.G. Merlot, and S.Y. Lee. A survey of search methodologies and automated system development for examination timetabling. Journal of Scheduling, 12(1):55-89, 2009. R. Qu, E. K. Burke, and B.McCollum. Adaptive automated construction of hybrid heuristics for exam timetabling and graph colouring problems. European Journal of Operational Research, 198(2):392-404, 2009. A.A. Shah, G. Folino, and N. Krasnogor. Towards high-throughput, multi-criteria protein structure comparison and analysis. IEEE Transactions on NanoBioscience, 9(2): 144-155, 2009. www.asap.cs.nott.ac.uk 31

M. Stout, J. Bacardit, J.D. Hirst, R.E. Smith, and N. Krasnogor. Prediction of topological contacts in proteins using learning classifier systems. Soft Computing - A Fusion of Foundations, Methodologies and Applications, 13(3):245-258, 2009. T. van Woensel and F. R. B. Cruz. A stochastic approach to traffic congestion costs. Computers & Operations Research, 36(5):1731-1739, 2009. Journal Papers in Press S. Abdul-Rahman, E. K. Burke, A. Bargiela, B. McCollum, and E. Özcan. A constructive approach to examination timetabling based on adaptive decomposition and ordering. Accepted for publication in Annals of Operations Research. J. A. D. Atkin, E. K. Burke, and J. S. Greenwood. TSAT allocation at London Heathrow: the relationship between slot compliance, throughput and equity. Accepted for publication in Public Transport. R. Bai, J. Blazewicz, E. K. Burke, G. Kendall, and B. McCollum. A simulated annealing hyper-heuristic methodology for flexible decision support. Accepted for publication in 4OR. R. Bai, G. Kendall, R. Qu, and J. Atkin. Tabu assisted guided local search approaches for freight service network design. Accepted for publication in Information Sciences. S. Bak, J. Blazewicz, G. Pawlak, M. Plaza, E. K. Burke, and G. Kendall. A parallel branch-and-bound approach to the rectangular guillotine strip cutting problem. Accepted for publication in INFORMS Journal on Computing. J. Blazewicz, E. K. Burke, G. Kendall, W. Mruczkiewicz, C. Oguz, and A. Swiercz. A hyper-heuristic approach to sequencing by hybridization of DNA sequences. Accepted for publication in Annals of Operations Research. E.K. Burke, T. Curtois, R. Qu, and G. Vanden Berghe. A time pre-defined variable depth search for nurse rostering. Accepted for publication in INFORMS Journal on Computing. E. K. Burke, M. Gendreau, M. Hyde, G. Kendall, G. Ochoa, E. Özcan, and R. Qu, Hyper-heuristics: A survey of the state of the art. Accepted for publication in Journal of the Operational Research Society. E. K. Burke, M. Hyde, G. Kendall, and J. Woodward. Grammatical evolution of local search heuristics. Accepted for publication in IEEE Transactions on Evolutionary Computation. E. K. Burke and M. R. Hyde, and G. Kendall A squeaky wheel optimisation methodology for two dimensional strip packing. Accepted for publication in Computers & Operations Research. E. K. Burke, M. Hyde, and G. Kendall. Automating the packing heuristic design process with genetic programming. Accepted for publication in Evolutionary Computation. E. K. Burke, G. Kendall, M. Mısır, and E. Özcan. Monte Carlo hyper-heuristics for examination timetabling, Accepted for publication in Annals of Operations Research. E. K. Burke, G. Kendall, and G. Whitwell. A simulated annealing enhancement of the best-fit heuristic for the orthogonal stock cutting problem. Accepted for publication in INFORMS Journal on Computing. E. K. Burke, J. Li, and R. Qu. Pareto-based search methodology for multi-objective nurse scheduling. Accepted for publication in Annals of Operations Research. E.K. Burke, N. Pham, R. Qu, J. Yellen. Linear combinations of heuristics for examination timetabling. Accepted for publication in Annals of Operations Research. P.K. Lehre and X. Yao. On the impact of mutation-selection balance on the runtime of evolutionary algorithms. Accepted for publication in IEEE Transactions on Evolutionary Computation. 32 ASAP Automated Scheduling, Optimisation and Planning Research Group

P.K. Lehre and X. Yao. Runtime analysis of the (1+1) EA on computing unique input output sequences. Accepted for publication in Information Sciences. J. Li, E. K. Burke, and R. Qu. A pattern recognition based intelligent search method: two case studies on the assignment problem. Accepted for publication in Applied Intelligence. J. Li, P. Hingston, and G. Kendall. Engineering design of strategies for winning iterated prisoner s dilemma competitions. Accepted for publication in IEEE Transactions on Computational Intelligence and AI in Games. B. McCollum, P. McMullan, A.J. Parkes, E.K. Burke, and R. Qu. A new model for automated examination timetabling. Accepted for publication in Annals of Operations Research. N. Mishra, S. Petrovic, and S. Sundar. A self-adaptive case-based reasoning system for dose planning in prostate cancer. Accepted for publication in Medical Physics. P. Moratori, S. Petrovic, and A. Vázquez-Rodríguez. Integrating rush orders into existent schedules for a complex job shop. Accepted for publication in Applied Intelligence. S. Petrovic and G. Vanden Berghe. A comparison of two approaches to nurse rostering problems. Accepted for publication in Annals of Operations Research. E. Özcan, A. J. Parkes, and A. Alkan. The interleaved constructive Memetic Algorithm and its application to timetabling. Accepted for publication in Computers & Operations Research. R. Qu, Y. Xu, J. Castro, and D. Landa-Silva. Particle swarm optimization for the steiner tree in graph and delay-constrained multicast routing problems. Accepted for publication in Journal of Heuristics. N.R. Sabar, M. Ayob, G. Kendall, and R. Qu. A Honey-bee mating optimization algorithm for educational timetabling problems. Accepted for publication in European Journal of Operational Research. N.R. Sabar, M. Ayob, G. Kendall, and R. Qu. A graph coloring constructive hyper-heuristic for examination timetabling problems. Accepted for publication in Applied Intelligence. J. Swan, G. Ochoa, G. Kendall, and M. Edjvet. Fitness landscapes and the Andrews-Curtis conjecture. Accepted for publication in International Journal of Algebra and Computation. H. Xing and R. Qu. A compact genetic algorithm for the network coding based resource minimization problem. Accepted for publication in Applied Intelligence. Y. Xu and R. Qu. A hybrid scatter search meta-heuristic for delay-constrained multicast routing problems. Accepted for publication in Applied Intelligence. Y. Xu and R. Qu. An iterative local search approach based on fitness landscapes analysis for the delay-constrained multicast routing problem. Accepted for publication in Computer Communications. Z. Zakaria and S. Petrovic. Genetic algorithms for match-up rescheduling of the flexible manufacturing systems. Accepted for publication in Computers & Industrial Engineering. Please refer to the main ASAP web page for a full list of publications: http://www.asap.cs.nott.ac.uk/ www.asap.cs.nott.ac.uk 33

Notes Grants Title Principal Investigator / Lead Scientist Co-Investigator(s) Funding Body Collaborator(s) Dates Total Amount Detection and Prediction of Lung Cancer using the znose with the Support Vector Machine classifier Handling Uncertainties in Transportation and Logistics Using Granular Computing and Hyperheuristics An investigation of the robustness of transportation scheduling for modern logistics. Dynamic Scheduling and Hyper-heuristic Approaches for Logistics Service Network Design and Fleet Scheduling Principled Application of Learning Classifier Systems to Large-Scale Challenging Datasets (LCSxLCD) Arelhi Bargiela, Isa, Ting MOSTI (01-02-12-SF0089) RM185,000 Bai Qu, Burke, Bargiela Ningbo Municipal Science and Technology Bureau, China Towards More Effective Computational Search Burke Kendall, Krasnogor, Parkes, Petrovic, Qu, Landa Silva Hybridising Exact and Heuristic Search Methods for Landing Operations at London Heathrow Bai Bargiela, Anberree Ningbo Municipal Natural Science Foundation, China 50,000 RMB Bai Kendall, Qu Zhejiang Provincial Natural Science Foundation (ZJNSF) 100,000 RMB 1/12/2009 to 31/05/2011 11/9/2008 to 31/12/2011 1/2/2008 to 28/2/2010 Tsinghua University 1/6/2010 to 31/5/2013 Bacardit EPSRC(EP/H016597/1) 1/6/2010 to 31/8/2011 Burke Atkin EPSRC through the Smith Institute for Industrial Mathematics and System Engineering 60,000 EPSRC(EP/H000968/1) 1/9/2009 to 31/08/2014 NATS ( 24,000) 1/10/2009 to 31/03/2013 Airport Systems Surface Management Burke Atkin SESAR 25,322 1/04/2009 to 1/03/2010 SANDPIT: Integrating and Automating Airport Operations Burke Stewart, Eftekhari, Zhong EPSRC(EP/H004424/1) Manchester Airport plc ( 10,000) and Zurich Airport ( 11,160) 1/10/2009 to 30/09/2013 39,360 Collaborative project with EEE-UNMC 10,000 This is a project awarded to the University of Nottingham Ningbo, China, funded by China Ningbo Municipal Natural Science Foundation 4,500 This is a project awarded to the University of Nottingham Ningbo, China, funded by China Ningbo Municipal Natural Science Foundation 9,500 This is a project awarded to the University of Nottingham Ningbo, China, funded by China Zhejiang Provincial Natural Science Foundation 101,458 EPSRC First Grant scheme 1,011,159 This is a renewal of our platform grant 84,000 This project is a CASE studentship which is being supported by National Air Traffic Services Ltd. 22,800 This project is funded under the SESAR initiative (Single European Sky ATM Research) which is funded by Eurocontrol and the European Commission. We are working on two sub-projects ( Enhanced Safety Nets and Enhanced Surface Routing ) with the NATMIG consortium which consists of SINTEF (Norway), Northrop Grumman Park Air Systems (Norway), SAAB (Sweden) and Airtel ATN (Ireland). We are collaborating with SINTEF on this project. 681,924 This EPSRC grant was awarded during an EPSRC sandpit event in November 2008. It represents a major collaboration between Manchester Airport, Zurich Airport and the Universities of Nottingham, Salford, Loughborough and Liverpool

Notes Title Principal Investigator / Lead Scientist Co-Investigator(s) Funding Body Collaborator(s) Dates Total Amount Enhanced Airport Collaborative Decision Making by integrating Passenger and Baggage Operations Investigating Automated Methodologies to Generate the Target Start-up Approval Time at London Heathrow Burke Atkin NATS 1/10/2009 to 31/03/2013 Burke Atkin NATS 1/4/2007 to present Optimisation Methods in Health Care Planning Burke Research Council of Norway NOK 625,000 ( 63,485) Next Generation Decision Support: Automating the Heuristic Design Process PLATFORM: Towards More General Optimisation/ Search Systems Investigating Automated Methodologies to Generate the Target Start-up Approval Time at London Heathrow Adaptive Multi-Objective Heuristic and Metaheuristic Approaches to Space Allocation The LANCS (Lancaster, Nottingham, Cardiff and Southampton) Initiative in Foundational Operational Research: Building Theory for Practice Models and Algorithms for Complex Scheduling Problems: A Visiting Fellowship BIOPTRAIN - Research Training Network for Bioinformatics Optimisation Towards a Framework for Modelling Variation in Automated Decision Support Hyper-heuristics for Scheduling, Rostering and Routing: An International Collaboration Maths TCC Follow-on-Fund: A National Taught Course Centre in Operational Research (NATCOR) Burke Landa Silva, Petrovic, Kendall, Garibaldi, Krasnogor, Qu Burke Kendall, Garibaldi, Petrovic, Krasnogor EPSRC (EP/D061571/1) 2,663,528 EPSRC (GR/S70197/01) 422,908 SINTEF 1/10/2007 to 30/9/2012 Burke NATS Ltd (formerly National Air Traffic Services Ltd) 37,800 Burke Kendall, Landa Silva EPSRC (GR/T26115/01) 205,378 Burke EPSRC S&I Award (EP/ F033214/1) Burke Garibaldi EPSRC (GR/T23374/01) 21,240 Garibaldi Burke, Krasnogor EU (FP6-IST-007597) 537,359 Garibaldi Burke EPSRC (EP/C542207/1) 143,282 Garibaldi Burke, Kendall EPSRC (EP/D027039/1) 31,828 Glazebrook Burke, Petrovic EPSRC (EP/J500938/1), 150,000 Real Time Solutions Ltd 112,500 Lancaster, Cardiff and Southampton Universities 1/10/2006 to 30/9/2011 1/2/2004 to 31/1/2009 1/4/2007 to 1/1/2009 8/4/2005 to 7/4/2009 01/09/08 to 31/8/2014 1/10/2004 to 30/9/2009 1/9/2005 to 31/8/2009 1/7/2006 to 30/6/2009 26/5/2006 to 25/5/2011 1/10/2011 to 30/09/2016 27,000 National Air Traffic Services Ltd are providing CASE studentship funding to support a University of Nottingham DTA award 30,500 63,485 This is a collaborative project with SINTEF, in Norway and the whole consortium received NOK 9,375,000 2,663,528 This is a major initiative to explore how decision support systems can design search methodologies 422,908 This is a prestigious Platform award 37,800 This is an investigation with National Air Traffic Services Ltd into how automated decision support could aid controllers at Heathrow with the start-up approval time allocation in advance 317,878 This is funded under EPSRC s Mathematics for Business initiative 1,988,920 This major EPSRC award is part of a 12M+ nitiative involving three other universities (Lancaster, Cardiff and Southampton). The initiative aims to build national capacity in Operational Research and to close the gap between theoretical OR and industrial practice. The consortium has received over 5.4M in total from EPSRC and the institutions have contributed over 7M. Nottingham s contribution is over 2.4M 21,240 This project supports a visiting fellowship for Prof. Peter Brucker, Osnabruck 537,359 This is a collaborative project with 4 other European institutions to support 12 PhD students, worth a total of over 2M across the consortium 143,282 This is a collaborative project with De Montfort University 31,828 This supports a visiting fellowship for Prof Michel Gendreau, Montreal 150,000 This is a continuation of the NATCOR taught PhD courses

Notes Title Principal Investigator / Lead Scientist Co-Investigator(s) Funding Body Collaborator(s) Dates Total Amount A National Taught Course Centre in Operational Research (NATCOR) Centre for Plant Integrative Biology: Novel Modelling Paradigms Monitoring and Prediction of Blood Sugar level for Diabetics through the use of intelligent software EP/E017975/1: An Investigation of Regulatory Decision Making by Automated Decision Makers EP/D031079/1: NETWORK: Interdisciplinary Cutting, Packing and Space Allocation Glazebrook Burke EPSRC (EP/E502067/1) 241,052 Hodgman Krasnogor BBSRC (BB/D019613/1) 500,768 Isa Bargiela, Arelhi, Ting MOSTI (01-02-12-SF0056) RM126,000 Kendall Pollard, Soane EPSRC (EP/E017975/1) 222,411 Dept for Env Food and Rural Affair Kendall Burke EPSRC Aptia Solutions Ltd, Gower Optimal Algorithms Ltd, JoTIKa (Midlands) Software Ltd, Real Time Solutions Ltd, SigmaTEK Europe Ltd 1/10/2006 to 30/9/2011 1/2/2007 to 31/1/2012 1/05/2010 to 30/11/2011 1/10/2006 to 31/10/2009 1/3/2006 to 28/02/2009 An Investigation of Collaborative Robotics Kendall activmedia 20,965 1/3/2006 to 28/2/2009 Bioinformatics, Systems and Synthetic Biology Plant Science Summer School (Semi) Formal Artificial Life Through P-systems & Learning Classifier Systems: An Investigation into InfoBiotics The Logistics of Small Things: a crossdisciplinnary feasibility account Evolutionary Optimisation of Self Assembling Nano- Designs (ExIStENcE) SynBioNT: A Synthetic Biology Network for Modelling and Programming Cell-Chell Interactions Plan, Develop and Implement a Telematics Based Predictive Maintenance System for Commercial Vehicles Towards More Effective Multi-objective Meta- Heuristics to Solve Complex Combinatorial Problems Krasnogor Bacardit, Bennett (Biosciences) European Science Foundation (ESF-2482) 60,435 Krasnogor EPSRC (EP/E017215/1) 515,565 Krasnogor Prof. M. Camara, Prof. E. K. Burke Krasnogor Prof. P. Beton, Prof. P. Moriarty, Prof. N. Champness EPSRC (EP/H024905/1) 202,805 EPSRC (EP/H010432/1) 945,423 Centre For Biomolecular Sciences, UoN Centre For Biomolecular Physics & Astronomy, UoN 18/3/2009 to 31/9/2009 1/9/2007 to 31/8/2010 1/11/2009 to 30/4/2012 1/2/2010 to 31/1/2013 Krasnogor Prof. C. Alexander BBSRC (BB/F01855X/1) Pharmacy, UoN 1/5/2008 to 30/4/2011 Landa Silva Kendall Technology Strategy Board Microlise Ltd 1/11/2011 to 31/10/2013 Landa Silva EPSRC (EP/E019781/1) 204,877 1/1/2007 to 31/12/2009 241,052 This is a UK-wide initiative to provide a high level of taught course PhD provision. It involves Lancaster, Nottingham, Southampton, Cardiff, Brunel and Warwick 500,768 This is part of the 9.2M Centre for Plant Integrative Biology 26,800 Collaborative project with EEE-UNMC 222,411 This is an EPSRC Ideas Factory 63,212 This is an EPSRC NETWORK 20,965 This project provides industrial support for a University of Nottingham funded CASE studentship 51,756 This covers the lodging and travel expenses of the 50 participants of an International Summer School. 515,565 This project investigates a new (semi) formal cellular Artificial Life methodology, which is called as InfoBiotics 202,805 This project investigates accelerating nanoscience, smart drugs automated programming, and optimising the life-cycle of synthetic biology projects 945,423 This proposal aims the development of novel evolutionary algorithms (EAs) and protocols, based on deeper principles than currently available, for the optimisation, design and exploitation of molecular self-assembly. 74,587 This network is funded by BBSRC (BB/F01855X/1) with co-funding from EPSRC and ESRC. 164,234 This project is a Knowledge Transfer Partnership (KTP No 8667) 204,877 This is funded under EPSRC s First Grant Scheme

Notes Title Principal Investigator / Lead Scientist Co-Investigator(s) Funding Body Collaborator(s) Dates Total Amount Developing Next Generation Rostering Software Using Advanced Scheduling Techniques Landa Silva Burke, Qu Technology Strategy Board Midland Software Limited 12/08/2008 to 15/02/2011 111,992 This project is a Knowledge Transfer Partnership (KTP No 7074) Design, Develop and Implement Modern Heuristic Algorithms for Improved, Adaptive Carrier, Management and Strategic Scheduling Landa Silva Kendall Technology Strategy Board 3t Logistics Ltd 1/01/2010 to 31/12/2011 124,672 This project is a Knowledge Transfer Partnership (KTP No 7449) Temporal and Spatial Pattern Recognition in Dynamic Networks Petrovic EPSRC Knowledge Transfer Secondments Programme 42,027 EADS-UK, Newport 1/12/2011 to 1/09/2012 111,772 This project has been awarded by the EPSRC Knowledge Transfer Secondments Programme which is a part of the Strategic Framework Agreement between the University of Nottingham and EPSRC Novel Approaches to Radiotherapy Planning and Scheduling in the NHS Petrovic Burke, Garibaldi EPSRC (EP/C549511/1) 268,315 Nottingham City Hospital and Walsgrave General Hospital 95,000 1/11/2005 to 28/2/2010 363,315 This is a collaborative project with Coventry University Hybrid Algorithms to Large Scale Portfolio Optimisation Qu Pont Industrial Mathematics Internship 1/1/2010 to 5/1/2010 8,130 This internship project is a collaborative project with NAG, Oxford to model and solve the complex large scale portfolio optimisation problems. CHELLnet: A Unifying Investigation in Artificial Cellularity and Complexity Whitaker Krasnogor EPSRC (EP/D023343/1) 81,737 1/10/2005 to 31/3/2009 81,737 This is an IDEAS Factory project collaborating with the Universities of Edinburgh, Glasgow, Imperial College London, Leeds, Manchester, Oxford and Southampton EU ( 589,115) BBSRC ( 575,355) EPSRC - Responsive Mode ( 4,402,569) EPSRC - Targeted Calls ( 5,813,607) Other ( 184,575) Industry ( 807,623) ASAP Funds by Source (Grants held during 2009-2011)

ASAP Personnel Academic Staff Sanja Petrovic Head of Group (0115) 95 14222 sxp@cs.nott.ac.uk www.cs.nott.ac.uk/~sxp/ Jason Atkin Science and Innovation Lecturer (0115) 95 14206 ekb@cs.nott.ac.uk www.cs.nott.ac.uk/~jaa/ Dario Landa-Silva Lecturer (0115) 84 66522 jds@cs.nott.ac.uk www.cs.nott.ac.uk/~jds/ Per Kristian Lehre Science and Innovation Lecturer (0115) 82 32823 pkl@cs.nott.ac.uk www.cs.nott.ac.uk/~pkl/ Ender Özcan Science and Innovation Lecturer (0115) 95 15544 exo@cs.nott.ac.uk www.cs.nott.ac.uk/~exo/ Andrew Parkes Science and Innovation Lecturer (0115) 95 14210 ajp@cs.nott.ac.uk www.cs.nott.ac.uk/~ajp/ Rong Qu Lecturer (0115) 84 66503 rxq@cs.nott.ac.uk www.cs.nott.ac.uk/~rxq/ 38 ASAP Automated Scheduling, Optimisation and Planning Research Group

China Campus Ruibin Bai Associate Professor Ningbo Campus, China +86 (0) 574 8818 0278 rzb@cs.nott.ac.uk www.cs.nott.ac.uk/~rzb/ Dr Jingpeng Li Lecturer +86 (0) 574 8818 6435 jpl@cs.nott.ac.uk www.cs.nott.ac.uk/~jpl/ John Woodward Lecturer +86 (0) 574 8818 0239 jrw@cs.nott.ac.uk www.cs.nott.ac.uk/~jrw/ Malaysia Campus Siang Yew Chong (UNMC) Lecturer Malaysia Campus +6 (03) 8924 8148 Siang-Yew.Chong@nottingham.edu.my baggins.nottingham.edu.my/~khczcsy/ Graham Kendall Vice Provost for Research and Knowledge Transfer & Professor of Computer Science +6 (03) 8924 8306 Graham.Kendall@nottingham.edu.my http://www.graham-kendall.com/ Administrative Staff Debbie Pitchfork ASAP Research Group Project Manager (0115) 84 66543 dap@cs.nott.ac.uk Senior Research Fellows Dr Matthew Hyde Dr Gabriela Ochoa www.asap.cs.nott.ac.uk 39

Research Associates Dr Yuri Bykov Dr Tim Curtois Dr Geert De Maere Dr Jiawei Li Dr Jerry Swan Dr Glenn Whitwell Dr Xia Xiaolei PhD Students Sam Allen Belal Ismail Khalil Al-Khateeb Stanislava Armstrong Amadeo Asco Zalilah Abd Aziz Monica Banerjea Elkin Castro Juan Pedro Castro Gutierrez Michael Clark John Drake Ha Duong Anas Elhag Enrico Glaab Sven Groenemeyer Qiang Guo 40 ASAP Automated Scheduling, Optimisation and Planning Research Group

PhD Students Nor Hayati Hamid Fang He Rob Hellier Joe Henry Obit Rupa Jagannathan Mohd Nizam Mohmad Kahar Ahmed Kheiri Khoi Le Mashael Maashi Jakub Marecek Nishikant Mishra Abdullah Muhammed Patrick Barbosa Moratori Tiago Pais Nam Pham Tim Pigden Syariza Abdul Rahman Stefan Ravizza Pedro Rocha Shamsudin MD Sarif Amr Soghier Saiful Izwan Suliman Ozgur Ulker Huanlai Xing Ying Xu www.asap.cs.nott.ac.uk 41

Visiting Fellows/Associated Staff Jacek Blazewicz Visiting Professor Peter Brucker EPSRC Visiting Fellow A. Şima Uyar Visiting Scholar Michel Gendreau EPSRC Visiting Fellow Barry McCollum Industrial Research Fellow Ceyda Oguz Visiting Professor Previous Members Jaume Bacardit School of Computer Science Lecturer Andrzej Bargiela School of Computer Science Professor of Computer Science (UNMC) Edmund K. Burke PVC for Research, University of Stirling Previous Head of Group Professor of Computer Science Natalio Krasnogor School of Computer Science Professor of Computer Science Nick Poxon ASAP Research Support Coordinator Ebru Tasci Administrative Assistant Dr Robert Oates Research Associate Dr Azhar Ali Shah Syed Research Associate Dr Leong Ting Lui Research Associate Dr German Terrazas Angulo Research Associate 42 ASAP Automated Scheduling, Optimisation and Planning Research Group

Previous Members Dr Jamie Twycross Research Associate Dr Pawel Widera Research Associate Jonathan Blakes PhD Student Jack Chaplin PhD Student Maria Franco PhD Student James Smaldon PhD Student Adam Sweetman School of Physics PhD Student How to Find Us See http://www.nottingham.ac.uk/computerscience/about/findingus.aspx for directions www.asap.cs.nott.ac.uk 43

Editors: Prof Graham Kendall and Dr Ender Özcan Automated Scheduling, Optimisation and Planning (ASAP) Research Group School of Computer Science The University of Nottingham Jubilee Campus, Wollaton Road Nottingham, NG8 1BB United Kingdom http://www.asap.ac.uk/ ASAP 2012 Designed and printed by Eden Design and Creation www.edendesignandcreation.com