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More About This Title Service Science
Making up a significant part of the world economy, the service sector is a rapidly evolving field that is relied on to dictate the public's satisfaction and success in various areas of everyday life, from banking and communications to education and healthcare. Service Science provides managers and students of the service industries with the quantitative skills necessary to model key decisions and performance metrics associated with services, including the management of resources, distribution of goods and services to customers, and the analysis and design of queueing systems.
The book begins with a brief introduction to the service sector followed by an introduction to optimization and queueing modeling, providing the methodological background needed to analyze service systems. Subsequent chapters present specific topics within service operations management, including:Location modeling and districtingResource allocation problemsShort- and long-term workforce managementPriority services, call center design, and customer schedulingInventory modelingVehicle routing
The author's own specialized software packages for location modeling, network optimization, and time-dependent queueing are utilized throughout the book, showing readers how to solve a variety of problems associated with service industries. These programs are freely available on the book's related web site along with detailed appendices and online spreadsheets that accompany the book's "How to Do It in Excel" sections, allowing readers to work hands-on with the presented techniques.
Extensively class-tested to ensure a comprehensive presentation, Service Science is an excellent book for industrial engineering and management courses on service operations at the upper-undergraduate and graduate levels. The book also serves as a reference for researchers in the fields of business, management science, operations research, engineering, and economics.
This book was named the 2010 Joint Publishers Book of the Year by the Institute of Industrial Engineers.
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.
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.
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.
3 Queueing theory.
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.
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.
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.
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.
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.
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.
9 Priority services, call center design and customer scheduling.
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.
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.
11 Where to from here?
11.2 Other methodologies.
11.3 Other applications in services.
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.
considered as a textbook for courses on service operations at the senior-undergraduate and graduate levels." (A Journal for the Worldwide Service Science Community, 2011)