This book addresses the many important problems in service operations management, which can be analyzed using two core methodologies: optimization and queueing theory (including numerical simulation of queues). After an introductory chapter on services, Chapter 2 provides a summary of optimization, and Chapter 3 discusses queueing theory. In addition to these two methodologically-based chapters, the book includes a lengthy review of probability (as an appendix). Chapters 4 through 11 present specific topics within service operations management, including location modeling, assignment problems,…mehr
This book addresses the many important problems in service operations management, which can be analyzed using two core methodologies: optimization and queueing theory (including numerical simulation of queues). After an introductory chapter on services, Chapter 2 provides a summary of optimization, and Chapter 3 discusses queueing theory. In addition to these two methodologically-based chapters, the book includes a lengthy review of probability (as an appendix). Chapters 4 through 11 present specific topics within service operations management, including location modeling, assignment problems, short and long-term workforce management, applications of queueing theory (particularly to call center design), inventory models, vehicle routing, pricing, and auctions. Chapter 12 provides a summary chapter that also outlines steps to utilize the disucssed concepts and methods in practive. The author's own SITATION software is utilized throughout the book in addition to a program that numerically solves time-dependent queueing problems. SITATION is a program that was originally included with the author's prior book, Network and Discrete Location: Models, Algorithms, and Applications. This software has been significantly updated over the years and has been rewritten from a DOS-based version to a version that operates under Windows. A Powerpoint overview of SITATION as well as a user-guide are included on the book's related web site. Chapter coverage includes: optimization; queueing theory; location models; assignment problems; short-term and long-term workforce scheduling; applications of queueing in services; inventory models; vehicle routing and services; pricing problems and combinatorial auctions for services; and an overview of probability.
MARK S. DASKIN, PhD, is Clyde W. Johnson Collegiate Professor and Chair of the Department of Industrial and Operations Engineering at the University of Michigan. A Fellow of both the Institute for Operations Research and the Management Sciences (INFORMS) and the Institute of Industrial Engineers (IIE), he has published extensively in his areas of research interest, which include supply chain network design, supply chain reliability, location modeling, healthcare operations research, and service operations management. Dr. Daskin is past-president of INFORMS and a past editor-in-chief of both Transportation Science and IIE Transactions. He is the author of Network and Discrete Location: Models, Algorithms, and Applications, also published by Wiley.
Inhaltsangabe
Preface. Acknowledgements. 1. Why study services? 1.1 What are services. 1.2 Services as a percent of the economy. 1.3 Public versus private service delivery. 1.4 Why model services? 1.5 Key service decisions. 1.6 Philosophy about models. 1.7 Outline of the book. 1.8 Problems. 1.9 References. METHODOLOGICAL FOUNDATIONS. 2 Optimization. 2.1 Introduction. 2.2 Five key elements of optimization. 2.3 Taxonomy of optimization models. 2.4 You probably have seen one already. 2.5 Linear programming. 2.6 Special network form. 2.7 Integer problems. 2.8 Multiple objective problems. 2.9 Mark's ten rules of formulating problems. 2.10 Problems. 2.11 References. 3 Queueing theory. 3.1 Introduction. 3.2 What is a queueing theory? 3.3 Key performance metrics for queues and Little's formula. 3.4 A framework for Markovian queues. 3.5 Key results for non-Markovian queues. 3.6 Solving queueing models numerically. 3.7 When conditions change over time. 3.8 Conclusions. 3.9 Problems. 3.10 References. APPLICATION AREAS. 4 Location and districting problems in services. 4.1 Example applications. 4.2 Taxonomy of location problems. 4.3 Covering problems. 4.4 Median problems - minimizing the demand-weighted average distance. 4.5 Multi-objective models. 4.6 Districting problems. 4.7 Franchise location problems. 4.8 Summary and software. 4.9 Problems. 4.10 References. 5 Inventory decisions in services. 5.1 Why is inventory in a service modeling book? 5.2 EOQ - a basic inventory model. 5.3 Extensions of the EOQ model. 5.4 Time varying demand. 5.5 Uncertain demand and lead times. 5.6 Newsvendor problem and applications. 5.7 Summary. 5.8 Problems. 5.9 References. 6 Resource allocation problems and decisions in services. 6.1 Example resource allocation problems. 6.2 How to formulate an assignment or resource allocation problem. 6.3 Infeasible solutions. 6.4 Assigning students to freshman seminars. 6.5 Assigning students to intersession courses. 6.6 Improving the assignment of zip codes to Congressional districts. 6.7 Summary. 6.8 Problems. 6.9 References. 7 Short-term workforce scheduling. 7.1 Overview of scheduling. 7.2 Simple model. 7.3 Extensions of the simple model. 7.4 More difficult extensions. 7.5 Linking scheduling to service. 7.6 Time-dependent queueing analyzer. 7.7 Assigning specific employees to shifts. 7.8 Summary. 7.9 Problems. 7.10 References. 8 Long-term workforce planning. 8.1 Why is long-term workforce planning an issue? 8.2 Basic model. 8.3 Grouping of skills. 8.4 Planning over time. 8.5 Linking to project scheduling. 8.6 Linking to personnel training and planning in general. 8.7 Simple model of training. 8.8 Summary. 8.9 Problems. 8.10 References. 9 Priority services, call center design and customer scheduling. 9.1 Examples. 9.2 Priority queueing for emergency and other services. service in each class with non-preemptive priorities. 9.2.3 Priority service with Poisson arrivals, multiple servers and identically distributed exponential service times.. 9.2.4 Preemptive queueing. 9.3 Call center design. 9.4 Scheduling in services. 9.5 Summary. 9.6 Problems. 9.7 References. 10 Vehicle routing and services. 10.1 Example routing problems. 10.2 Classification of routing problems. 10.3 Arc routing. 10.4 The traveling salesman problem. 10.5 Vehicle routing problems. 10.6 Summary. 10.7 Problems. 10.8 References. 11 Where to from here? 11.1 Introduction. 11.2 Other methodologies. 11.3 Other applications in services. 11.4 Summary. 11.5 References. APPENDICES. A. Sums of series - basic formulae. B. Overview of probability. B.1. Introduction and basic definitions. B.2 Axioms of probability .. B.3 Joint, marginal and conditional probabilities and Bayes' theorem. B.4 Counting, ordered pairs, permutations and combinations. B.5 Random variables. B.6 Discrete random variables. B.7 Continuous random variables. B.8 Moment and probability generating functions. B.9 Generating random variables. B.10 Random variables in Excel. C. References.
Preface. Acknowledgements. 1. Why study services? 1.1 What are services. 1.2 Services as a percent of the economy. 1.3 Public versus private service delivery. 1.4 Why model services? 1.5 Key service decisions. 1.6 Philosophy about models. 1.7 Outline of the book. 1.8 Problems. 1.9 References. METHODOLOGICAL FOUNDATIONS. 2 Optimization. 2.1 Introduction. 2.2 Five key elements of optimization. 2.3 Taxonomy of optimization models. 2.4 You probably have seen one already. 2.5 Linear programming. 2.6 Special network form. 2.7 Integer problems. 2.8 Multiple objective problems. 2.9 Mark's ten rules of formulating problems. 2.10 Problems. 2.11 References. 3 Queueing theory. 3.1 Introduction. 3.2 What is a queueing theory? 3.3 Key performance metrics for queues and Little's formula. 3.4 A framework for Markovian queues. 3.5 Key results for non-Markovian queues. 3.6 Solving queueing models numerically. 3.7 When conditions change over time. 3.8 Conclusions. 3.9 Problems. 3.10 References. APPLICATION AREAS. 4 Location and districting problems in services. 4.1 Example applications. 4.2 Taxonomy of location problems. 4.3 Covering problems. 4.4 Median problems - minimizing the demand-weighted average distance. 4.5 Multi-objective models. 4.6 Districting problems. 4.7 Franchise location problems. 4.8 Summary and software. 4.9 Problems. 4.10 References. 5 Inventory decisions in services. 5.1 Why is inventory in a service modeling book? 5.2 EOQ - a basic inventory model. 5.3 Extensions of the EOQ model. 5.4 Time varying demand. 5.5 Uncertain demand and lead times. 5.6 Newsvendor problem and applications. 5.7 Summary. 5.8 Problems. 5.9 References. 6 Resource allocation problems and decisions in services. 6.1 Example resource allocation problems. 6.2 How to formulate an assignment or resource allocation problem. 6.3 Infeasible solutions. 6.4 Assigning students to freshman seminars. 6.5 Assigning students to intersession courses. 6.6 Improving the assignment of zip codes to Congressional districts. 6.7 Summary. 6.8 Problems. 6.9 References. 7 Short-term workforce scheduling. 7.1 Overview of scheduling. 7.2 Simple model. 7.3 Extensions of the simple model. 7.4 More difficult extensions. 7.5 Linking scheduling to service. 7.6 Time-dependent queueing analyzer. 7.7 Assigning specific employees to shifts. 7.8 Summary. 7.9 Problems. 7.10 References. 8 Long-term workforce planning. 8.1 Why is long-term workforce planning an issue? 8.2 Basic model. 8.3 Grouping of skills. 8.4 Planning over time. 8.5 Linking to project scheduling. 8.6 Linking to personnel training and planning in general. 8.7 Simple model of training. 8.8 Summary. 8.9 Problems. 8.10 References. 9 Priority services, call center design and customer scheduling. 9.1 Examples. 9.2 Priority queueing for emergency and other services. service in each class with non-preemptive priorities. 9.2.3 Priority service with Poisson arrivals, multiple servers and identically distributed exponential service times.. 9.2.4 Preemptive queueing. 9.3 Call center design. 9.4 Scheduling in services. 9.5 Summary. 9.6 Problems. 9.7 References. 10 Vehicle routing and services. 10.1 Example routing problems. 10.2 Classification of routing problems. 10.3 Arc routing. 10.4 The traveling salesman problem. 10.5 Vehicle routing problems. 10.6 Summary. 10.7 Problems. 10.8 References. 11 Where to from here? 11.1 Introduction. 11.2 Other methodologies. 11.3 Other applications in services. 11.4 Summary. 11.5 References. APPENDICES. A. Sums of series - basic formulae. B. Overview of probability. B.1. Introduction and basic definitions. B.2 Axioms of probability .. B.3 Joint, marginal and conditional probabilities and Bayes' theorem. B.4 Counting, ordered pairs, permutations and combinations. B.5 Random variables. B.6 Discrete random variables. B.7 Continuous random variables. B.8 Moment and probability generating functions. B.9 Generating random variables. B.10 Random variables in Excel. C. References.
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