Curriculum Vitae Nima Safaei Address: Bombardier Aerospace 123 Garratt Boulevard Toronto ON Canada M3K 1Y5 Emails: nima.safaei@aero.bombardier.com, Safaei@mie.utoronto.ca, Homepage: http://individual.utoronto.ca/nima_safaei Office: 416 373 5990 Ext. 35990 Education: B.S.: Applied Mathematics, Department of Mathematics, Mazandaran University, Babolsar, Iran, 1995 1999. M.S.: System and Industrial Engineering, Department of Industrial Engineering, Mazandaran University of Science and Technology, Babol, Iran, 2000 2002. PhD: System and Industrial Engineering, Department of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran, 2003 2006. Detailed skills: Applied Operations Research (Mathematical modeling, Optimization methods, Simulation), Operations Management (Production Planning and Inventory Control), Layout Design and Facility location/allocation, Industry Scheduling (Production, Maintenance tasks, Workforce, Job shop), Routing problems, Logistics, Transportation (Network Analysis). Work Experiences Senior Specialist: Department of Maintenance and Reliability Engineering, Bombardier Aerospace (started at January 2011). Postdoctoral Fellow: Center for Maintenance Optimization and Reliability Engineering (C MORE), Department of Mechanical and Industrial Engineering, University of Toronto, Canada, October 2007 August 2010. Researcher (Visiting Scholar): Department of Mechanical Engineering, University of British Colombia, Vancouver, Canada, February September, 2007. Informatics expert: Management and Planning Organization, Gorgan, Iran, 2002 2003 Courses Taught: Department of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran, 2005: Instructor for Production Planning course (B.S). Department of Industrial Engineering, Mazandaran University of Science and Technology, Babol, Iran, 2006: Instructor for Meta heuristic and Combinatorial Optimization course (M.S). Department of Industrial Engineering, Industrial Management Institute, Gorgan, Iran, 2006: Instructor for Production Management course (M.S). Department of Industrial Engineering, University of Shomal, Amol, Iran, 2006: Instructor for Inventory Control course (B.S). Invited referee/reviewer for more than 30 peer reviewed scholarly journals. Software and Programming Experiences: Strong Skill in: Visual Basic. NET, VBA, LINGO, Microsoft Office Relative Skill in: C#, SQL Server, Matlab, and Cplex 1
Prototype Software Development A number of prototype software packages has been developed to solve the real world optimization problems such as Production scheduling, maintenance tasks scheduling, crew planning, vehicle routing, asset life cycle costs estimation, and aircraft maintenance routing. Flexible Flow line Scheduling Fleet Routing & Distribution Management Maintenance Scheduling Estimation of asset lifecycle costs using simulation Aircraft Maintenance Routing and Tasks Assignment Representative Projects Aircraft Maintenance Routing, Bombardier Aerospace Inc., Toronto, Ontario, Canada, since January 2011. The aircraft maintenance routing problem (AMRP) is a challenging optimization problem for commercial airline operations. Given a short horizon, the AMRP determines the route of each individual aircraft in a sequence of revenue flights, so that it will have sufficient maintenance opportunities (Time on Ground in a maintenance station) to perform the due maintenance tasks. Cyclic rotation is a dominant policy in the literature on the aircraft maintenance routing in which the generic n days routes are constructed ignoring the operational background of planes and full range of the maintenance requirements. This policy does not consider many facts: the planes differ in age, utilization rate and maintenance history while the maintenance tasks vary in duration and check interval which is defined in terms of different flight attributes. Further, the domestic airlines mostly have a non routine flight schedule. The purpose of this project is to present an integrated decision module that considers above facts to determine the week length route per aircraft, consolidate the maintenance tasks into the work packages, and assign them to the maintenance opportunities existing in the route. Restoration workforce Planning, Hydro One Inc. (Electricity Delivery Company), Toronto, Ontario, Canada, 2008. The project is for annual planning the maintenance workforce of Hydro one, an electricity distribution company in Ontario. Internal and external workforces are employed to perform maintenance actions and restore power after interruptions throughout the province. According to the electricity distribution network, the province is divided into a number of operating centers (OP), each having local crews to perform maintenance actions and fix power interruptions. However, determining the size of the crew in each OP and also for each month is challenging. The reason for this is that the frequency of the interruptions differs from one OP to another and from one month to another because it is affected by various factors such as system configuration, deterioration and failure of the equipment, weather conditions, etc. The company would like to know how many internal and external workers should be available during the year to cover possible interruptions across the province with minimum cost and minimum interruption duration. 2
Workforce constrained Maintenance scheduling using a computational intelligence based approach, Dofasco Inc. (steel producer), Hamilton, Ontario, Canada, 2007. The project is related to Dofasco Inc., Ontario, Canada, which recently moved to a plant wide scheduling approach through a central department, called the Central Services department (CSD), to respond to the maintenance requirements of manufacturing/business areas (MAs) in the plant. The aim of this department is to minimize the workforce costs and avoid long term disruptions and shutdowns of the equipment within MAs. Each MA schedules its maintenance jobs and submits them to CSD which attempts to schedule the workforce to meet needs across the plant. The problem is a bi objective maintenance scheduling problem with the aim of simultaneously minimizing the workforce requirements and maximizing the equipment availability. The skilled workforce is provided by internal and external resources using regular time, overtime and contracting. The equipment availability is measured by the downtime required for preventive maintenance (scheduled) and failure repair (unscheduled) jobs. We also encounter imminent or potential failures whose priorities depend on the severity of the failure on the system (secondary failure). Maintenance scheduling for Aircraft Fleet, Ministry of Defense, U.K, 2008. The project is related to the operation of a fleet of aircraft with a certain flying program in which the availability of the aircraft sufficient to meet the flying program is a challenging issue. During the pre or after flight inspections, some component failures of the aircraft(s) may be found. In such cases, the aircraft(s) are sent to the repair shop to be scheduled as maintenance jobs, consisting of failure repairs or preventive maintenance tasks. The objective is to schedule the jobs in such a way that sufficient number of aircrafts is available for the next flight programs. The main resource, as well as the main constraint, in the shop is skilled workforce. Estimation of the Asset Lifecycle Costs using Mont Carlo Simulation technique, Hydro One Inc. (Electricity Delivery Company), Toronto, Ontario, Canada, 2008. The objective of the project was to forecast future Hydro One s OM&A costs for all assets including transformers and breakers. OM&A costs include the Preventive Maintenance (PM), Corrective Maintenance (CM), Overhaul, and end of life/removal costs. Each of above costs has different characteristics and associated dynamics. My responsibility was to develop ad hoc simulation software to solve the mathematical model for estimating mentioned costs. The model s parameters are based on the historical data, related published reports, papers and Hydro One s experts knowledge. Vehicle Routing Problem (VRP) for the staff transportation fleet, Khuzestan Steel Company, Ahvaz, Iran, 2004 2005. The company policy involved the pick up and drop off of all hourly employees. The project was to optimize the fleet routes with the aim of minimizing the fleet travelling costs and maximizing the personnel satisfaction. Storage Space Allocation Problem in Shahid Rajaei Container Terminal, Ports and Shipping Organization, Tehran, Iran, 2005. The problem is defined as the temporary allocation of the inbound/outbound containers to the storage blocks at each time period with aim of balancing the workload between the blocks in order to minimize the storage/retrieval times of containers. The containers storage/retrieval time is an important efficiency criterion to measure the performance of a terminal. There are different types (as well as different sizes) of containers consisting of regular, empty and refrigerated containers. The difference between types of containers is often resulted from the difference between goods and items inside them such as foods, chemical substances, liquids, etc. This issue means that similar containers must be (or must not be) allocated to the same block, or a certain type of container must be (or must not be) allocated to a certain block. 3
Representative Publications and Conference Presentations [1] N. Safaei, Reza Tavakkoli Moghaddam and Corey Kiassat, A hybrid particle swarm optimization to solve the redundant reliability problems with multiple component choices, accepted for publication in Applied Soft Computing, 2012. (DOI:10.1016/j.asoc.2012.07.020) [2] N. Safaei, A. Zuashkiani, Manufacturing System Design Considering Multiple Machine Replacement under Discounted Costs, IIE Transactions, Vol. 44, pp. 1100 1114, 2012 (http://www.tandfonline.com/doi/abs/10.1080/0740817x.2012.654845). [3] N. Safaei, D. Banjevic and A.K.S. Jardine, Workforce Planning for Power Restoration in Electricity Delivery Industry: an Integrated Simulation Optimization Approach, IEEE Transactions on Power Systems, Vol. 27, No. 1, pp. 442 449, 2012 (http://dx.doi.org/10.1109/tpwrs.2011.2166090) [4] N. Safaei, D. Banjevic and A.K.S. Jardine, Workforce constrained Maintenance Scheduling for Military Aircraft Fleet: A Case Study, Annals of Operations Research, Vol. 186, No. 1, pp. 295 316, 2011(10.1007/s10479 011 0885 4) [5] N. Safaei, D. Banjevic and A.K.S. Jardine, Multi Threaded Simulated Annealing for a biobjective Workforce constrained Maintenance Scheduling Problem, International Journal of Production Research, 2011 (http://dx.doi.org/10.1080/00207543.2011.571444) [6] N. Safaei, D. Banjevic and A.K.S. Jardine, Bi objective Workforce constrained Maintenance Scheduling: A Case Study, Journal of Operational Research Society, Vol. 62, pp. 1005 1018, 2011 (http://dx.doi.org/10.1057/jors.2010.51) [7] N. Safaei, D. Banjevic and A.K.S. Jardine, Impact of the Use based Maintenance Policy on the Performance of Cellular Manufacturing Systems, International Journal of Production Research, vol. 48, No. 8, pp. 2233 2260, 2010 (http://dx.doi.org/10.1080/00207540802710273) [8] N. Safaei, M. Bazzazi, and P. Assadi, An Integrated Storage Space and Berth Allocation Problem in a Container Terminal, International Journal of Mathematics in Operational Research, vol. 2, No. 6, pp. 674 693, 2010 (http://dx.doi.org/10.1504/ijmor.2010.035494) [9] N. Safaei, Reza Tavakkoli Moghaddam and Farrokh Sassani, A Series Parallel Redundant Reliability System for the Cellular Manufacturing Design, Proceedings of the Institution of Mechanical Engineers, Part O, Journal of Risk and Reliability, vol. 223, No. 3, pp. 233 250, 2009. [10] N. Safaei, R. Tavakkoli Moghaddam, Integrated multi period cell formation and subcontracting production planning in dynamic cellular manufacturing systems, International Journal of Production Economics, Vol. 120, No. 2, pp. 301 314, 2009 (10.1016/j.ijpe.2008.12.013) [11] N. Safaei, R. Tavakkoli Moghaddam, An Extended Fuzzy Parametric Programming based Approach for Designing Cellular Manufacturing Systems under Uncertainty and Dynamic Conditions, International Journal of Computer Integrated Manufacturingg. vol. 22, No. 6, pp. 538 548, 2009 (DOI: 10.1080/09511920802616773) [12] N. Safaei, M. Saidi Mehrabad, R. Tavakkoli Moghaddam and F. Sassani, A Fuzzy Programming Approach to a Cell Formation Problem with Dynamic and Uncertain Conditions, Journal of Fuzzy Sets and Systems, vol. 159, pp. 215 236, 2008 (http://dx.doi.org/10.1016/j.fss.2007.06.014) [13] N. Safaei, M. Saidi Mehrabad, M.S. Jabal Ameli, A hybrid simulated annealing for solving an extended model of dynamic cellular manufacturing system, European Journal of Operational Research, vol. 185 (2), pp 563 592, 2008 (http://dx.doi.org/10.1016/j.ejor.2006.12.058) [14] N. Safaei, M. Saidi Mehrabad and M. Babakhani, Designing cellular manufacturing systems under dynamic and uncertain conditions, Journal of Intelligent Manufacturing, Vol. 18, pp. 383 399, 2007 (http://dx.doi.org/10.1007/s10845 007 0029 5) [15] N. Safaei, S.J. Sadjadi and M. Babakhani, An efficient genetic algorithm for determining the optimal price discrimination, Applied Mathematics and Computation, Vol. 181(2), pp. 1693 1702, 2006 (10.1016/j.amc.2006.03.022) [16] N. Safaei, Aircraft Maintenance Routing Using Detailed Maintenance Program, INFORMS Annual Meeting, Charlotte, NC, U.S.A., 13 16 November, 2011 4
[17] N. Safaei, Dragan Banjevic and Andrew K.S. Jardine, Workforce constrained Maintenance Scheduling for Aircraft Fleet: A Case Study, Proceedings of 16th ISSAT International Conference on Reliability and Quality in Design, Washington D.C., U.S.A., 5 7 August, 2010, pp. 291 297. [18] N. Safaei, Behzad Ghodrati, Maintenance Workforce Management: A Case Study, Proceeding of the 1st International Congress on e Maintenance, Lulea, Sweden, 22 24 June, 2010, pp. 38 45. [19] N. Safaei and Andrew K.S. Jardine, A Parallel Simulated Annealing for a Multi objective Maintenance Workforce Scheduling Problem, 9th CORS INFORMS International meeting, Toronto, 14 17, June, 2009. [20] N. Safaei, Dragan Banjevic and Andrew K.S. Jardine, Multi objective Maintenance Workforce Scheduling in a Steel Company, 13th IFAC Symposium on Information Control Problems in Manufacturing (InCom09), Moscow, 3 5, June, 2009. [21] N. Safaei, Dragan Banjevic and Andrew K.S. Jardine, Economic Life of Capital Equipments in a Cellular Manufacturing System, 13th IFAC Symposium on Information Control Problems in Manufacturing (InCom09), Moscow, 3 5, June, 2009. [22] N. Safaei, Dragan Banjevic and Andrew K.S. Jardine, Modeling a Multi objective Maintenance Workforce Scheduling Problem: A case Study, CORS/Optimization Conference, Quebec: Canada, May 12 14, 2008. [23] N. Safaei and R. Tavakkoli Moghaddam, Reliability consideration in a cell formation problem with parallel series configuration, Proceeding of the 3rd International Conference on Group Technology / Cellular Manufacturing, Groningen: Netherlands, July 3 5, 2006, pp. 36 43. [24] N. Safaei and R. Tavakkoli Moghaddam, The use of genetic algorithms for multi mode resource constrained project planning with the diminishing returns, Proceeding of the 5th International Symposium on Intelligent Manufacturing Systems, Sakarya, Turkey, May 29 31, 2006, pp. 216 226. [25] N. Safaei, R. Tavakkoli Moghaddam and S. Jabal Ameli, A generalized cell formation problem in dynamic environment with different inter and intra cell batch sizes, Proceeding of The 12th IFAC Symposium on Information Control problems in Manufacturing, Saint Etienne, France, May 15 19, 2006, Vol. 2, pp. 401 406. Invited Speaker/Instructor: [1] The application of Artificial Intelligence in Transportation Science, ASCE Student Chapter and Advanced Transpiration Research Workshop, The Department of Civil Engineering, The Catholic University of America, Washington DC, March 22, 2011. [2] Scheduling Maintenance Jobs under Skilled Workforce Availability Constraint in Steel Company, International Maintenance Excellence Conference, September 21 24, 2010, Toronto, Canada. [3] Resource Planning and Maintenance Task Scheduling Under Workforce Constraint, International Physical Asset Management Conference, October 9 12, 2010, Tehran, Iran [4] Effective Use of Maintenance Resources, Scheduling and Planning, Physical Asset Management Certificate Program, C MORE Lab, University of Toronto, Nov 09, 2009, Nov 04, 2010, Nov 11, 2011, Toronto. References 1. A.K.S. Jardine, PhD, P.Eng, Department of Mechanical and Industrial Engineering, University of Toronto, ON, Canada. jardine@mie.utoronto.ca. Tel: +1 416 978 2921. 2. F. Sasani, PhD, P.Eng, Department of Mechanical Engineering, the University of British Colombia, Vancouver, B.C, Canada. sassani@mech.ubc.ca. Tel: +1 604 822 6671. 5