THROUGHPUT OPTIMIZATION IN ROBOTIC CELLS


 Amie Young
 1 years ago
 Views:
Transcription
1 Contents Preface xv 1. ROBOTIC CELLS IN PRACTICE Cellular Manufacturing Robotic Cell Flowshops Throughput Optimization Historical Overview Applications A CLASSIFICATION SCHEME FOR ROBOTIC CELLS AND NOTATION Machine Environment Number of Machines Number of Robots Types of Robots Cell Layout Processing Characteristics Pickup Criterion TravelTime Metric Number of PartTypes Objective Function An α β γ Classification for Robotic Cells Cell Data Processing Times Loading and Unloading Times Notations for Cell States and Robot Actions CYCLIC PRODUCTION Operating Policies and Dominance of Cyclic Solutions 29 ix
2 x THROUGHPUT OPTIMIZATION IN ROBOTIC CELLS 3.2 Cycle Times Waiting Times Computation of Cycle Times Lower Bounds on Cycle Times Optimal 1Unit Cycles Special Cases General Cases: Constant TravelTime Cells Optimization over Basic Cycles General Cases: Time Cells Additive and Euclidean Travel Calculation of Makespan of a Lot A Graphical Approach Algebraic Approaches Quality of 1Unit Cycles and Approximation Results Additive TravelTime Cells Pyramidal Cycles A 1.5Approximation Algorithm A 10/7Approximation for Additive Cells Constant TravelTime Cells A 1.5Approximation Algorithm Euclidean TravelTime Cells DUALGRIPPER ROBOTS Additional Notation Cells with Two Machines A Cyclic Sequence for mmachine DualGripper Cells DualGripper Cells with Small Gripper Switch Times Comparing DualGripper and SingleGripper Cells Comparison of Productivity: Computational Results Efficiently Solvable Cases SingleGripper Cells with Output Buffers at Machines DualGripper Robotic Cells: Constant Travel Time Lower Bounds and Optimal Cycles: mmachine Simple Robotic Cells OneUnit Cycles MultiUnit Cycles PARALLEL MACHINES SingleGripper Robots Definitions kunit Cycles and Blocked Cycles 156
3 Contents xi Structural Results for kunit Cycles Blocked Cycles LCM Cycles Practical Implications Optimal Cycle for a Common Case Fewest Machines Required to Meet Timelines DualGripper Robots Lower Bound on Per Unit Cycle Time An Optimal Cycle Improvement from Using a DualGripper Robot or Parallel Machines Installing a DualGripper Robot in a Simple Robotic Cell Installing Parallel Machines in a SingleGripper Robot Cell Installing a DualGripper Robot in a SingleGripper Robotic Cell with Parallel Machines An Illustration on Data from Implemented Cells MULTIPLEPARTTYPE PRODUCTION: SINGLEGRIPPER ROBOTS MPS Cycles and CRM Sequences Scheduling Multiple PartTypes in TwoMachine Cells Scheduling Multiple PartTypes in ThreeMachine Cells Cycle Time Derivations Efficiently Solvable Special Cases SteadyState Analyses Reaching Steady State for the Sequence CRM(π 2 ) Reaching Steady State for the Sequence CRM(π 6 ) A Practical Guide to Initializing Robotic Cells Intractable Cycles for ThreeMachine Cells MPS Cycles with the Sequence CRM(π 2 ) MPS Cycles with the Sequence CRM(π 6 ) Complexity of ThreeMachine Robotic Cells Scheduling Multiple PartTypes in Large Cells Class U: Schedule Independent Problems Class V 1: Special Cases of the TSP Class V 2: NPHard TSP Problems Class W : NPHard NonTSP Problems Overview Heuristics for ThreeMachine Problems A Heuristic Under the Sequence CRM(π 2 ) 270
4 xii THROUGHPUT OPTIMIZATION IN ROBOTIC CELLS A Heuristic Under the Sequence CRM(π 6 ) Computational Testing Heuristics for General ThreeMachine Problems Heuristics for Large Cells The Cell Design Problem Forming Cells Buffer Design An Example Computational Testing MULTIPLEPARTTYPE PRODUCTION: DUALGRIPPER ROBOTS TwoMachine Cells: Undominated CRM Sequences TwoMachine Cells: Complexity Cycle Time Calculation Strong NPCompleteness Results Polynomially Solvable Problems Analyzing TwoMachine Cells with Small Gripper Switch Times A Heuristic for Specific CRM Sequences A Performance Bound for Heuristic HardCRM A Heuristic for TwoMachine Cells Comparison of Productivity: SingleGripper Vs. Dual Gripper Cells An Extension to mmachine Robotic Cells MULTIPLEROBOT CELLS Physical Description of a MultipleRobot Cell Cycles in MultipleRobot Cells Cycle Times Scheduling by a Heuristic Dispatching Rule Computational Results Applying an LCM Cycle to Implemented Cells NOWAIT AND INTERVAL ROBOTIC CELLS NoWait Robotic Cells Interval Pickup Robotic Cells OPEN PROBLEMS Simple Robotic Cells Simple Robotic Cells with Multiple Part Types 376
5 Contents xiii 10.3 Robotic Cells with Parallel Machines Stochastic Data DualGripper Robots Flexible Robotic Cells Implementation Issues Using Local Material Handling Devices Revisiting Machines 379 Appendices Appendix A 383 A.1 1Unit Cycles 383 A Unit Cycles in Classical Notation 384 A Unit Cycles in Activity Notation 385 Appendix B 387 B.1 The GilmoreGomory Algorithm for the TSP 387 B.1.1 The TwoMachine NoWait Flowshop Problem 387 B.1.2 Formulating a TSP 388 B.1.3 The GilmoreGomory Algorithm 389 B.2 The ThreeMachine NoWait Flowshop Problem as a TSP 394 Copyright Permissions 409 Index 413
6
vii TABLE OF CONTENTS CHAPTER TITLE PAGE DECLARATION DEDICATION ACKNOWLEDGEMENT ABSTRACT ABSTRAK
vii TABLE OF CONTENTS CHAPTER TITLE PAGE DECLARATION DEDICATION ACKNOWLEDGEMENT ABSTRACT ABSTRAK TABLE OF CONTENTS LIST OF TABLES LIST OF FIGURES LIST OF ABBREVIATIONS LIST OF SYMBOLS LIST OF APPENDICES
More informationApproximability of TwoMachine NoWait Flowshop Scheduling with Availability Constraints
Approximability of TwoMachine NoWait Flowshop Scheduling with Availability Constraints T.C. Edwin Cheng 1, and Zhaohui Liu 1,2 1 Department of Management, The Hong Kong Polytechnic University Kowloon,
More informationClassification  Examples
Lecture 2 Scheduling 1 Classification  Examples 1 r j C max given: n jobs with processing times p 1,...,p n and release dates r 1,...,r n jobs have to be scheduled without preemption on one machine taking
More informationClassification  Examples 1 1 r j C max given: n jobs with processing times p 1,..., p n and release dates
Lecture 2 Scheduling 1 Classification  Examples 11 r j C max given: n jobs with processing times p 1,..., p n and release dates r 1,..., r n jobs have to be scheduled without preemption on one machine
More informationResearch Article Batch Scheduling on TwoMachine Flowshop with MachineDependent Setup Times
Hindawi Publishing Corporation Advances in Operations Research Volume 2009, Article ID 153910, 10 pages doi:10.1155/2009/153910 Research Article Batch Scheduling on TwoMachine Flowshop with MachineDependent
More information! Solve problem to optimality. ! Solve problem in polytime. ! Solve arbitrary instances of the problem. #approximation algorithm.
Approximation Algorithms 11 Approximation Algorithms Q Suppose I need to solve an NPhard problem What should I do? A Theory says you're unlikely to find a polytime algorithm Must sacrifice one of three
More informationPlanning and Scheduling in Manufacturing and Services
Michael L. Pinedo Planning and Scheduling in Manufacturing and Services Second edition 4y Springer Preface Contents of CDROM vii xvii Part I Preliminaries 1 Introduction 3 1.1 Planning and Scheduling:
More information! Solve problem to optimality. ! Solve problem in polytime. ! Solve arbitrary instances of the problem. !approximation algorithm.
Approximation Algorithms Chapter Approximation Algorithms Q Suppose I need to solve an NPhard problem What should I do? A Theory says you're unlikely to find a polytime algorithm Must sacrifice one of
More informationFactors to Describe Job Shop Scheduling Problem
Job Shop Scheduling Job Shop A work location in which a number of general purpose work stations exist and are used to perform a variety of jobs Example: Car repair each operator (mechanic) evaluates plus
More informationManufacturing Planning and Control for Supp Chain Management
Manufacturing Planning and Control for Supp Chain Management Sixth Edition F. Robert Jacobs Indiana University William L. Berry The Ohio State University (Emeritus) D. Clay Whybark University of North
More informationMakespan Computation for Cyber Manufacturing Centre Using Bottleneck Analysis: A Reentrant Flow Shop Problem
IMECS 008, 9 March, 008, Hong Kong Makespan Computation for Cyber Manufacturing Centre Using Bottleneck Analysis: A Reentrant Flow Shop Problem Salleh Ahmad Bareduan and Sulaiman H. Hasan Abstract This
More informationJUSTINTIME SCHEDULING WITH PERIODIC TIME SLOTS. Received December May 12, 2003; revised February 5, 2004
Scientiae Mathematicae Japonicae Online, Vol. 10, (2004), 431 437 431 JUSTINTIME SCHEDULING WITH PERIODIC TIME SLOTS Ondřej Čepeka and Shao Chin Sung b Received December May 12, 2003; revised February
More informationManufacturing Planning and Control for Supply Chain Management
Manufacturing Planning and Control for Supply Chain Management APICS/CPIM Certification Edition F. Robert Jacobs Indiana University William L. Berry The Ohio State University (Emeritus) D.ClayWhybark University
More informationA review of lot streaming in a flow shop environment with makespan criteria
6th International Conference on Industrial Engineering and Industrial Management. XVI Congreso de Ingeniería de Organización. Vigo, July 1820, 2012 A review of lot streaming in a flow shop environment
More informationInteger Programming Approach to Printed Circuit Board Assembly Time Optimization
Integer Programming Approach to Printed Circuit Board Assembly Time Optimization Ratnesh Kumar Haomin Li Department of Electrical Engineering University of Kentucky Lexington, KY 405060046 Abstract A
More informationChapter 11. 11.1 Load Balancing. Approximation Algorithms. Load Balancing. Load Balancing on 2 Machines. Load Balancing: Greedy Scheduling
Approximation Algorithms Chapter Approximation Algorithms Q. Suppose I need to solve an NPhard problem. What should I do? A. Theory says you're unlikely to find a polytime algorithm. Must sacrifice one
More informationObjective Criteria of Job Scheduling Problems. Uwe Schwiegelshohn, Robotics Research Lab, TU Dortmund University
Objective Criteria of Job Scheduling Problems Uwe Schwiegelshohn, Robotics Research Lab, TU Dortmund University 1 Jobs and Users in Job Scheduling Problems Independent users No or unknown precedence constraints
More informationSoftware Performance and Scalability
Software Performance and Scalability A Quantitative Approach Henry H. Liu ^ IEEE )computer society WILEY A JOHN WILEY & SONS, INC., PUBLICATION Contents PREFACE ACKNOWLEDGMENTS xv xxi Introduction 1 Performance
More informationTABLE OF CONTENTS CHAPTER NO. TITLE PAGE NO. ABSTRACT iii LIST OF TABLES LIST OF FIGURES LIST OF ABBREVIATIONS
ix TABLE OF CONTENTS CHAPTER NO. TITLE PAGE NO. ABSTRACT iii LIST OF TABLES x LIST OF FIGURES xii LIST OF ABBREVIATIONS xiv 1 INTRODUCTION 1 1.1 ENTERPRISE RESOURCE PLANNING (ERP) AN OVERVIEW 1 1.2 AIM
More informationCloud Computing. and Scheduling. DataIntensive Computing. Frederic Magoules, Jie Pan, and Fei Teng SILKQH. CRC Press. Taylor & Francis Group
Cloud Computing DataIntensive Computing and Scheduling Frederic Magoules, Jie Pan, and Fei Teng SILKQH CRC Press Taylor & Francis Group Boca Raton London New York CRC Press is an imprint of the Taylor
More informationR u t c o r Research R e p o r t. A Method to Schedule Both Transportation and Production at the Same Time in a Special FMS.
R u t c o r Research R e p o r t A Method to Schedule Both Transportation and Production at the Same Time in a Special FMS Navid Hashemian a Béla Vizvári b RRR 32011, February 21, 2011 RUTCOR Rutgers
More information11. APPROXIMATION ALGORITHMS
11. APPROXIMATION ALGORITHMS load balancing center selection pricing method: vertex cover LP rounding: vertex cover generalized load balancing knapsack problem Lecture slides by Kevin Wayne Copyright 2005
More informationMINIMIZING THE TOTAL COMPLETION TIME IN A TWO STAGE FLOW SHOP WITH A SINGLE SETUP SERVER
MINIMIZING THE TOTAL COMPLETION TIME IN A TWO STAGE FLOW SHOP WITH A SINGLE SETUP SERVER A THESİS SUBMITTED TO THE DEPARTMENT OF INDUSTRIAL ENGINEERING AND THE GRADUATE SCHOOL OF ENGINEERING AND SCIENCE
More informationAssembly line balancing to minimize balancing loss and system loss. D. Roy 1 ; D. Khan 2
J. Ind. Eng. Int., 6 (11), 1, Spring 2010 ISSN: 173702 IAU, South Tehran Branch Assembly line balancing to minimize balancing loss and system loss D. Roy 1 ; D. han 2 1 Professor, Dep. of Business Administration,
More informationNPcomplete? NPhard? Some Foundations of Complexity. Prof. Sven Hartmann Clausthal University of Technology Department of Informatics
NPcomplete? NPhard? Some Foundations of Complexity Prof. Sven Hartmann Clausthal University of Technology Department of Informatics Tractability of Problems Some problems are undecidable: no computer
More informationHYBRID GENETIC ALGORITHMS FOR SCHEDULING ADVERTISEMENTS ON A WEB PAGE
HYBRID GENETIC ALGORITHMS FOR SCHEDULING ADVERTISEMENTS ON A WEB PAGE Subodha Kumar University of Washington subodha@u.washington.edu Varghese S. Jacob University of Texas at Dallas vjacob@utdallas.edu
More informationTABLE OF CONTENT CHAPTER TITLE PAGE TITLE DECLARATION DEDICATION ACKNOWLEDGEMENTS ABSTRACT ABSTRAK
TABLE OF CONTENT CHAPTER TITLE PAGE TITLE DECLARATION DEDICATION ACKNOWLEDGEMENTS ABSTRACT ABSTRAK TABLE OF CONTENT LIST OF TABLES LIST OF FIGURES LIST OF ABBREVIATIONS LIST OF APPENDICES i ii iii iv v
More informationDongPing Song. Optimal Control and Optimization. of Stochastic. Supply Chain Systems. 4^ Springer
DongPing Song Optimal Control and Optimization Supply Chain Systems of Stochastic 4^ Springer Contents 1 Stochastic Supply Chain Systems 1 1.1 Introduction 1 1.2 Uncertainties'in Supply Chain Systems
More informationComplexity Theory. IE 661: Scheduling Theory Fall 2003 Satyaki Ghosh Dastidar
Complexity Theory IE 661: Scheduling Theory Fall 2003 Satyaki Ghosh Dastidar Outline Goals Computation of Problems Concepts and Definitions Complexity Classes and Problems Polynomial Time Reductions Examples
More informationMIPBased Approaches for Solving Scheduling Problems with Batch Processing Machines
The Eighth International Symposium on Operations Research and Its Applications (ISORA 09) Zhangjiajie, China, September 20 22, 2009 Copyright 2009 ORSC & APORC, pp. 132 139 MIPBased Approaches for Solving
More informationCMPSCI611: Approximating MAXCUT Lecture 20
CMPSCI611: Approximating MAXCUT Lecture 20 For the next two lectures we ll be seeing examples of approximation algorithms for interesting NPhard problems. Today we consider MAXCUT, which we proved to
More informationSimultaneous Scheduling of Machines and Material Handling System in an FMS
Simultaneous Scheduling of Machines and Material Handling System in an FMS B. Siva Prasad Reddy* and C.S.P. Rao** *Department of Mech. Engg., KITS, Warangal5 5 (A.P) INDIA. **Department of Mech. Engg.,
More informationNetwork Security A Decision and GameTheoretic Approach
Network Security A Decision and GameTheoretic Approach Tansu Alpcan Deutsche Telekom Laboratories, Technical University of Berlin, Germany and Tamer Ba ar University of Illinois at UrbanaChampaign, USA
More informationApplied Algorithm Design Lecture 5
Applied Algorithm Design Lecture 5 Pietro Michiardi Eurecom Pietro Michiardi (Eurecom) Applied Algorithm Design Lecture 5 1 / 86 Approximation Algorithms Pietro Michiardi (Eurecom) Applied Algorithm Design
More informationContents. 1 Introduction. 2 Feature List. 3 Feature Interaction Matrix. 4 Feature Interactions
1 Introduction 1.1 Purpose and Scope................................. 1 1 1.2 Organization..................................... 1 2 1.3 Requirements Notation............................... 1 2 1.4 Requirements
More informationOffline sorting buffers on Line
Offline sorting buffers on Line Rohit Khandekar 1 and Vinayaka Pandit 2 1 University of Waterloo, ON, Canada. email: rkhandekar@gmail.com 2 IBM India Research Lab, New Delhi. email: pvinayak@in.ibm.com
More information1 st year / 20142015/ Principles of Industrial Eng. Chapter 3 / Dr. May G. Kassir. Chapter Three
Chapter Three Scheduling, Sequencing and Dispatching 31 SCHEDULING Scheduling can be defined as prescribing of when and where each operation necessary to manufacture the product is to be performed. It
More informationWAFER SCHEDULING ALGORITHMS HIGH THROUGHPUT, HIGH FLEXIBILITY OR BOTH?
WAFER SCHEDULING ALGORITHMS HIGH THROUGHPUT, HIGH FLEXIBILITY OR BOTH? Gary Choquette SUSS MicroTec Lithography GmbH Germany Dr. Thomas Grund SUSS MicroTec Lithography GmbH Germany Published in the SUSS
More informationA Comparison of Oracle Performance on Physical and VMware Servers
A Comparison of Oracle Performance on Physical and VMware Servers By Confio Software Confio Software 4772 Walnut Street, Suite 100 Boulder, CO 80301 3039388282 www.confio.com Comparison of Physical and
More informationLIST OF FIGURES. Figure No. Caption Page No.
LIST OF FIGURES Figure No. Caption Page No. Figure 1.1 A Cellular Network.. 2 Figure 1.2 A Mobile Ad hoc Network... 2 Figure 1.3 Classifications of Threats. 10 Figure 1.4 Classification of Different QoS
More informationBatch Scheduling for Identical MultiTasks Jobs on Heterogeneous Platforms
atch Scheduling for Identical MultiTasks Jobs on Heterogeneous Platforms JeanMarc Nicod (JeanMarc.Nicod@lifc.univfcomte.fr) Sékou iakité, Laurent Philippe  16/05/2008 Laboratoire d Informatique de
More informationProgramming Using Python
Introduction to Computation and Programming Using Python Revised and Expanded Edition John V. Guttag The MIT Press Cambridge, Massachusetts London, England CONTENTS PREFACE xiii ACKNOWLEDGMENTS xv 1 GETTING
More informationTHE CERTIFIED SIX SIGMA BLACK BELT HANDBOOK
THE CERTIFIED SIX SIGMA BLACK BELT HANDBOOK SECOND EDITION T. M. Kubiak Donald W. Benbow ASQ Quality Press Milwaukee, Wisconsin Table of Contents list of Figures and Tables Preface to the Second Edition
More informationOperation of Manufacturing Systems with Workinprocess Inventory and Production Control
Operation of Manufacturing Systems with Workinprocess Inventory and Production Control YuanHung (Kevin) Ma, Yoram Koren (1) NSF Engineering Research Center for Reconfigurable Manufacturing Systems,
More informationIMPROVING THE EFFICIENCY OF HUB OPERATIONS IN A LESSTHANTRUCKLOAD DISTRIBUTION NETWORK
IMPROVING THE EFFICIENCY OF HUB OPERATIONS IN A LESSTHANTRUCKLOAD DISTRIBUTION NETWORK Amy M. Brown Thesis submitted to the Faculty of the Virginia Polytechnic Institute and State University in partial
More informationSIMS 255 Foundations of Software Design. Complexity and NPcompleteness
SIMS 255 Foundations of Software Design Complexity and NPcompleteness Matt Welsh November 29, 2001 mdw@cs.berkeley.edu 1 Outline Complexity of algorithms Space and time complexity ``Big O'' notation Complexity
More informationGPU for Scientific Computing. Ali Saleh
1 GPU for Scientific Computing Ali Saleh Contents Introduction What is GPU GPU for Scientific Computing KMeans Clustering Knearest Neighbours When to use GPU and when not Commercial Programming GPU
More informationNPCompleteness and Cook s Theorem
NPCompleteness and Cook s Theorem Lecture notes for COM3412 Logic and Computation 15th January 2002 1 NP decision problems The decision problem D L for a formal language L Σ is the computational task:
More informationThe Classes P and NP. mohamed@elwakil.net
Intractable Problems The Classes P and NP Mohamed M. El Wakil mohamed@elwakil.net 1 Agenda 1. What is a problem? 2. Decidable or not? 3. The P class 4. The NP Class 5. TheNP Complete class 2 What is a
More informationSwitching and Finite Automata Theory
Switching and Finite Automata Theory Understand the structure, behavior, and limitations of logic machines with this thoroughly updated third edition. New topics include: CMOS gates logic synthesis logic
More informationQUANTITATIVE METHODS. for Decision Makers. Mik Wisniewski. Fifth Edition. FT Prentice Hall
Fifth Edition QUANTITATIVE METHODS for Decision Makers Mik Wisniewski Senior Research Fellow, Department of Management Science, University of Strathclyde Business School FT Prentice Hall FINANCIAL TIMES
More informationIntroducción a Calendarización en Sistemas Paralelas, Grids y Nubes
CICESE Research Center Ensenada, Baja California Mexico Introducción a Calendarización en Sistemas Paralelas, Grids y Nubes Dr. Andrei Tchernykh CICESE Centro de Investigación Científica y de Educación
More informationPractical Hadoop. Security. Bhushan Lakhe
Practical Hadoop Security Bhushan Lakhe Contents J About the Author About the Technical Reviewer Acknowledgments Introduction xiii xv xvii xix Part I: Introducing Hadoop and Its Security 1 Chapter 1: Understanding
More informationComputer Algorithms. NPComplete Problems. CISC 4080 Yanjun Li
Computer Algorithms NPComplete Problems NPcompleteness The quest for efficient algorithms is about finding clever ways to bypass the process of exhaustive search, using clues from the input in order
More informationScheduling Shop Scheduling. Tim Nieberg
Scheduling Shop Scheduling Tim Nieberg Shop models: General Introduction Remark: Consider non preemptive problems with regular objectives Notation Shop Problems: m machines, n jobs 1,..., n operations
More informationSERVICE MANAGEMENT AN INTEGRATED APPROACH TO SUPPLY CHAIN MANAGEMENT AND OPERATIONS. Cengiz Haksever Barry Render
SERVICE MANAGEMENT AN INTEGRATED APPROACH TO SUPPLY CHAIN MANAGEMENT AND OPERATIONS Cengiz Haksever Barry Render Preface CONTENTS xxi Part I: Understanding Services 1 THE IMPORTANT ROLE SERVICES PLAY IN
More informationTutorial 8. NPComplete Problems
Tutorial 8 NPComplete Problems Decision Problem Statement of a decision problem Part 1: instance description defining the input Part 2: question stating the actual yesorno question A decision problem
More informationIntroduction to Learning & Decision Trees
Artificial Intelligence: Representation and Problem Solving 538 April 0, 2007 Introduction to Learning & Decision Trees Learning and Decision Trees to learning What is learning?  more than just memorizing
More informationCurriculum Vitae. B.M.T. Lin, NCTU, TW
Curriculum Vitae Bertrand MiaoTsong Lin ( 林 妙 聰 ) Gender: Male Marital status: Married (1 son and 1 daughter) Date of Birth: May 4, 1964 Nationality: Taiwan, ROC Affiliation: Institute of Information
More informationSoftware Performance and Scalability. A Quantitative Approach. Quantitative Software Engineering Series
Brochure More information from http://www.researchandmarkets.com/reports/2174945/ Software Performance and Scalability. A Quantitative Approach. Quantitative Software Engineering Series Description: Praise
More informationBusiness Architecture
Business Architecture A Practical Guide JONATHAN WHELAN and GRAHAM MEADEN GOWER Contents List of Figures List of Tables About the Authors Foreword Preface Acknowledgemen ts Abbreviations IX xi xiii xv
More informationA SIMULATION STUDY FOR DYNAMIC FLEXIBLE JOB SHOP SCHEDULING WITH SEQUENCEDEPENDENT SETUP TIMES
A SIMULATION STUDY FOR DYNAMIC FLEXIBLE JOB SHOP SCHEDULING WITH SEQUENCEDEPENDENT SETUP TIMES by Zakaria Yahia Abdelrasol Abdelgawad A Thesis Submitted to the Faculty of Engineering at Cairo University
More informationScheduling Single Machine Scheduling. Tim Nieberg
Scheduling Single Machine Scheduling Tim Nieberg Single machine models Observation: for nonpreemptive problems and regular objectives, a sequence in which the jobs are processed is sufficient to describe
More informationHeuristic Methods. Part #1. João Luiz Kohl Moreira. Observatório Nacional  MCT COAA. Observatório Nacional  MCT 1 / 14
Heuristic Methods Part #1 João Luiz Kohl Moreira COAA Observatório Nacional  MCT Observatório Nacional  MCT 1 / Outline 1 Introduction Aims Course's target Adviced Bibliography 2 Problem Introduction
More informationHidden Markov Models
8.47 Introduction to omputational Molecular Biology Lecture 7: November 4, 2004 Scribe: HanPang hiu Lecturer: Ross Lippert Editor: Russ ox Hidden Markov Models The G island phenomenon The nucleotide frequencies
More informationCOPYRIGHTED MATERIAL. Contents. List of Figures. Acknowledgments
Contents List of Figures Foreword Preface xxv xxiii xv Acknowledgments xxix Chapter 1 Fraud: Detection, Prevention, and Analytics! 1 Introduction 2 Fraud! 2 Fraud Detection and Prevention 10 Big Data for
More informationLoad Balancing for Sustainable ICT
Load Balancing for Sustainable ICT AlexandruAdrian Tantar alexandru.tantar@uni.lu Emilia Tantar emilia.tantar@uni.lu Pascal Bouvry pascal.bouvry@uni.lu ABSTRACT The herein paper addresses the issue of
More informationW4118 Operating Systems. Instructor: Junfeng Yang
W4118 Operating Systems Instructor: Junfeng Yang Outline Introduction to scheduling Scheduling algorithms 1 Direction within course Until now: interrupts, processes, threads, synchronization Mostly mechanisms
More informationRevenue Management and Survival Analysis in the Automobile Industry
Andre Jerenz Revenue Management and Survival Analysis in the Automobile Industry With a foreword by Prof. Dr. Ulrich Tushaus GABLER EDITION WISSENSCHAFT List of Figures List of Tables Nomenclature xiii
More informationAN INTRODUCTION TO MANAGEMENT SCIENCE QUANTITATIVE APPROACHES TO DECISION MAKING. David R. Anderson. University of Cincinnati. Dennis J.
2008 AGIInformation Management Consultants May be used for personal purporses only or by libraries associated to dandelon.com network. E L E V E N T H E D I T I O N AN INTRODUCTION TO MANAGEMENT SCIENCE
More informationEfficient and Robust Allocation Algorithms in Clouds under Memory Constraints
Efficient and Robust Allocation Algorithms in Clouds under Memory Constraints Olivier Beaumont,, Paul RenaudGoud Inria & University of Bordeaux Bordeaux, France 9th Scheduling for Large Scale Systems
More informationLoad Balancing and Rebalancing on Web Based Environment. Yu Zhang
Load Balancing and Rebalancing on Web Based Environment Yu Zhang This report is submitted as partial fulfilment of the requirements for the Honours Programme of the School of Computer Science and Software
More informationIndustrial Optimization
Industrial Optimization Lessons learned from Optimization in Practice Marco Lübbecke Chair of Operations Research RWTH Aachen University, Germany SICS Stockholm Feb 11, 2013 Discrete Optimization: Some
More informationCPSC 211 Data Structures & Implementations (c) Texas A&M University [ 313]
CPSC 211 Data Structures & Implementations (c) Texas A&M University [ 313] File Structures A file is a collection of data stored on mass storage (e.g., disk or tape) Why on mass storage? too big to fit
More informationApplied Multivariate Analysis
Neil H. Timm Applied Multivariate Analysis With 42 Figures Springer Contents Preface Acknowledgments List of Tables List of Figures vii ix xix xxiii 1 Introduction 1 1.1 Overview 1 1.2 Multivariate Models
More informationOptimal Scheduling for Dependent Details Processing Using MS Excel Solver
BULGARIAN ACADEMY OF SCIENCES CYBERNETICS AND INFORMATION TECHNOLOGIES Volume 8, No 2 Sofia 2008 Optimal Scheduling for Dependent Details Processing Using MS Excel Solver Daniela Borissova Institute of
More informationDesign of Enterprise Systems
Design of Enterprise Systems Theory, Architecture, and Methods Ronald E. Giachetti CRC Press Taylor &. Francis Group Boca Raton London New York CRC Press is an imprint of the Taylor & Francis Group, an
More informationObservations on PCB Assembly Optimization
Observations on PCB Assembly Optimization A hierarchical classification scheme based on the number of machines (one or many) and number of boards (one or many) can ease PCB assembly optimization problems.
More informationFundamentals of Actuarial Mathematics
Fundamentals of Actuarial Mathematics S. David Promislow York University, Toronto, Canada John Wiley & Sons, Ltd Contents Preface Notation index xiii xvii PARTI THE DETERMINISTIC MODEL 1 1 Introduction
More informationBandwidth management for WDM EPONs
Vol. 5, No. 9 / September 2006 / JOURNAL OF OPTICAL NETWORKING 637 Bandwidth management for WDM EPONs Michael P. McGarry and Martin Reisslein Department of Electrical Engineering, Arizona State University,
More informationScheduling Problem of JobShop with Blocking: A Taboo Search Approach
MIC 20014th Metaheuristics International Conference 643 Scheduling Problem of JobShop with Blocking: A Taboo Search Approach Yazid Mati Nidhal Rezg Xiaolan Xie INRIA/MACSI Project & LGIPM ENIMILE DU
More informationSingle machine models: Maximum Lateness 12 Approximation ratio for EDD for problem 1 r j,d j < 0 L max. structure of a schedule Q...
Lecture 4 Scheduling 1 Single machine models: Maximum Lateness 12 Approximation ratio for EDD for problem 1 r j,d j < 0 L max structure of a schedule 0 Q 1100 11 00 11 000 111 0 0 1 1 00 11 00 11 00
More informationContents. Introduction and System Engineering 1. Introduction 2. Software Process and Methodology 16. System Engineering 53
Preface xvi Part I Introduction and System Engineering 1 Chapter 1 Introduction 2 1.1 What Is Software Engineering? 2 1.2 Why Software Engineering? 3 1.3 Software LifeCycle Activities 4 1.3.1 Software
More informationA MultiObjective Performance Evaluation in Grid Task Scheduling using Evolutionary Algorithms
A MultiObjective Performance Evaluation in Grid Task Scheduling using Evolutionary Algorithms MIGUEL CAMELO, YEZID DONOSO, HAROLD CASTRO Systems and Computer Engineering Department Universidad de los
More informationChapter 8. Operations Scheduling
Chapter 8 Operations Scheduling Buffer Soldering Visual Inspection Special Stations Buffer workforce Production Management 161 Scheduling is the process of organizing, choosing and timing resource usage
More informationlife science data mining
life science data mining  '.)'. < } ti» (>.:>,u» c ~'editors Stephen Wong Harvard Medical School, USA ChungSheng Li /BM Thomas J Watson Research Center World Scientific NEW JERSEY LONDON SINGAPORE.
More informationBatch Scheduling of Deteriorating Products
Decision Making in Manufacturing and Services Vol. 1 2007 No. 1 2 pp. 25 34 Batch Scheduling of Deteriorating Products Maksim S. Barketau, T.C. Edwin Cheng, Mikhail Y. Kovalyov, C.T. Daniel Ng Abstract.
More information5 Scheduling. Operations Planning and Control
5 Scheduling Operations Planning and Control Some Background Machines (resources) are Machines process jobs (molding machine, x ray machine, server in a restaurant, computer ) Machine Environment Single
More informationHighMix LowVolume Flow Shop Manufacturing System Scheduling
Proceedings of the 14th IAC Symposium on Information Control Problems in Manufacturing, May 2325, 2012 HighMix LowVolume low Shop Manufacturing System Scheduling Juraj Svancara, Zdenka Kralova Institute
More informationMINIMUM FLOW TIME SCHEDULE GENETIC ALGORITHM FOR MASS CUSTOMIZATION MANUFACTURING USING MINICELLS
University of Kentucky UKnowledge University of Kentucky Master's Theses Graduate School 2006 MINIMUM FLOW TIME SCHEDULE GENETIC ALGORITHM FOR MASS CUSTOMIZATION MANUFACTURING USING MINICELLS Phanindra
More informationHigh Performance Computing for Operation Research
High Performance Computing for Operation Research IEF  Paris Sud University claude.tadonki@upsud.fr INRIAAlchemy seminar, Thursday March 17 Research topics Fundamental Aspects of Algorithms and Complexity
More informationResearch Paper Business Analytics. Applications for the Vehicle Routing Problem. Jelmer Blok
Research Paper Business Analytics Applications for the Vehicle Routing Problem Jelmer Blok Applications for the Vehicle Routing Problem Jelmer Blok Research Paper Vrije Universiteit Amsterdam Faculteit
More informationProduction and Operations. Management Systems
Production and Operations Management Systems Sushil Gupta and Martin Starr CRC Press Taylor & Francis Croup Boca Raton London New York CRC Press is an imprint of the Taylor & Francis Group, an informa
More informationQuantum and Nondeterministic computers facing NPcompleteness
Quantum and Nondeterministic computers facing NPcompleteness Thibaut University of Vienna Dept. of Business Administration Austria Vienna January 29th, 2013 Some pictures come from Wikipedia Introduction
More informationContents. List of Figures. List of Tables. Acknowledgments PART I INTRODUCTION 1
List of Figures List of Tables Acknowledgments Preface xv xix xxi xxiii PART I INTRODUCTION 1 1 The Evolution of Financial Analysis 3 1.1 Bookkeeping 3 1.2 Modern finance 8 1.3 Departments, silos and analysis
More informationThe Conference Call Search Problem in Wireless Networks
The Conference Call Search Problem in Wireless Networks Leah Epstein 1, and Asaf Levin 2 1 Department of Mathematics, University of Haifa, 31905 Haifa, Israel. lea@math.haifa.ac.il 2 Department of Statistics,
More informationThe Trip Scheduling Problem
The Trip Scheduling Problem Claudia Archetti Department of Quantitative Methods, University of Brescia Contrada Santa Chiara 50, 25122 Brescia, Italy Martin Savelsbergh School of Industrial and Systems
More informationVehicle Routing and Scheduling. Martin Savelsbergh The Logistics Institute Georgia Institute of Technology
Vehicle Routing and Scheduling Martin Savelsbergh The Logistics Institute Georgia Institute of Technology Vehicle Routing and Scheduling Part I: Basic Models and Algorithms Introduction Freight routing
More informationHeuristic Algorithms for Open Shop Scheduling to Minimize Mean Flow Time, Part I: Constructive Algorithms
Heuristic Algorithms for Open Shop Scheduling to Minimize Mean Flow Time, Part I: Constructive Algorithms Heidemarie Bräsel, André Herms, Marc Mörig, Thomas Tautenhahn, Jan Tusch, Frank Werner OttovonGuerickeUniversität,
More information