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This text is an introduction to Operations Management. Three themes are woven throughout the book: optimization or trying to do the best we can, managing tradeoffs between conflicting objectives, and dealing with uncertainty. After a brief introduction, the text reviews the fundamentals of probability including commonly used discrete and continuous distributions and functions of a random variable. The next major section, beginning in Chapter 7, examines optimization. The key fundamentals of optimization—inputs, decision variables, objective(s), and constraints—are introduced. Optimization is…mehr
This text is an introduction to Operations Management. Three themes are woven throughout the book: optimization or trying to do the best we can, managing tradeoffs between conflicting objectives, and dealing with uncertainty. After a brief introduction, the text reviews the fundamentals of probability including commonly used discrete and continuous distributions and functions of a random variable. The next major section, beginning in Chapter 7, examines optimization. The key fundamentals of optimization—inputs, decision variables, objective(s), and constraints—are introduced. Optimization is applied to linear regression, basic inventory modeling, and the newsvendor problem, which incorporates uncertain demand. Linear programming is then introduced. We show that the newsvendor problem can be cast as a network flow linear programming problem. Linear programming is then applied to the problem of redistributing empty rental vehicles (e.g., bicycles) at the end of a day and the problem of assigning students to seminars. Several chapters deal with location models as examples of both simple optimization problems and integer programming problems. The next major section focuses on queueing theory including single-and multi-server queues. This section also introduces a numerical method for solving for key performance metrics for a common class of queueing problems as well as simulation modeling. Finally, the text ends with a discussion of decision theory that again integrates notions of optimization, tradeoffs, and uncertainty analysis. The text is designed for anyone with a modest mathematical background. As such, it should be readily accessible to engineering students, economics, statistics, and mathematics majors, as well as many business students.
Mark S. Daskin is the immediate past Department Chair of the Industrial and Operations Engineering Department at the University of Michigan. He holds the Clyde W. Johnson Collegiate Professorship. Prior to joining the faculty at Michigan in 2010, Daskin was on the faculty at Northwestern University (for 30 years) and the University of Texas (for a year and a half ). He received his Ph.D. from the Civil Engineering Department at M.I.T. in 1978. He also holds a B.S.C.E. degree from that department and a Certificate of Post-Graduate Study in Engineering from the University of Cambridge in England. His research focuses on the application and development of operations research techniques for the analysis of health care problems, as well as transportation, supply chain, and manufacturing problems. He is the author of over 80 refereed papers and of two books: Network and Discrete Location: Models, Algorithms and Applications ( John Wiley, 1995; second edition, 2013) and Service Science ( JohnWiley, 2010), winner of the IIE Joint Publishers Book of the Year Award in 2011. Daskin received the Frank and Lillian Gilbreth Award from the Institute of Industrial and Systems Engineers in 2021. He was elected to the U.S. National Academy of Engineering in 2017. He is a Fellow of both INFORMS and IIE and has received the David F. Baker Distinguished Research Award, the Technical Innovation Award and the Fred C. Crane Award for Distinguished Service from IIE, as well as the Kimball Medal for service to the society and the profession from INFORMS. He received the Lifetime Achievement Award in Location Analysis from the Section on Location Analysis of INFORMS in 2014. He is a past editor-in-chief of both IIE Transaction and Transportation Science. In 2006, he was the president of INFORMS. He served as the chair of the Department of Industrial Engineering and Management Sciences at Northwestern University from 1995–2001.
Inhaltsangabe
List of Figures.- List of Tables.- Preface.- Acknowledgments.- Introduction to Operations Management.- Fundamentals of Uncertainty Analysis.- Intuition About Probability.- Discrete Probability Distributions.- Continuous Probability Distributions.- Functions of a Random Variable.- Fundamentals of Optimization.- Basic Inventory Management.- Inventory Management with Uncertain Demand.- Introduction to Linear Programming.- The Transportation Problem.- Assigning Students to Seminars.- Analytic Location Modeling.- Minimizing the Average Distance to a Facility.- A Facility Location Tradeoff.- Fundamentals of Queueing Theory.- A Single-Server Queue.- A More General Single-Server Queue and The Impact of Variability on Queueing Performance.- A Simple Multi-Server Queue.- Solving Queueing Equations Numerically and Simulating the Performance of a Queue.- Decision Theory.- Summary, Where to Next, and Final Thoughts.- Index.- Author's Biography.
List of Figures.- List of Tables.- Preface.- Acknowledgments.- Introduction to Operations Management.- Fundamentals of Uncertainty Analysis.- Intuition About Probability.- Discrete Probability Distributions.- Continuous Probability Distributions.- Functions of a Random Variable.- Fundamentals of Optimization.- Basic Inventory Management.- Inventory Management with Uncertain Demand.- Introduction to Linear Programming.- The Transportation Problem.- Assigning Students to Seminars.- Analytic Location Modeling.- Minimizing the Average Distance to a Facility.- A Facility Location Tradeoff.- Fundamentals of Queueing Theory.- A Single-Server Queue.- A More General Single-Server Queue and The Impact of Variability on Queueing Performance.- A Simple Multi-Server Queue.- Solving Queueing Equations Numerically and Simulating the Performance of a Queue.- Decision Theory.- Summary, Where to Next, and Final Thoughts.- Index.- Author's Biography.
List of Figures.- List of Tables.- Preface.- Acknowledgments.- Introduction to Operations Management.- Fundamentals of Uncertainty Analysis.- Intuition About Probability.- Discrete Probability Distributions.- Continuous Probability Distributions.- Functions of a Random Variable.- Fundamentals of Optimization.- Basic Inventory Management.- Inventory Management with Uncertain Demand.- Introduction to Linear Programming.- The Transportation Problem.- Assigning Students to Seminars.- Analytic Location Modeling.- Minimizing the Average Distance to a Facility.- A Facility Location Tradeoff.- Fundamentals of Queueing Theory.- A Single-Server Queue.- A More General Single-Server Queue and The Impact of Variability on Queueing Performance.- A Simple Multi-Server Queue.- Solving Queueing Equations Numerically and Simulating the Performance of a Queue.- Decision Theory.- Summary, Where to Next, and Final Thoughts.- Index.- Author's Biography.
List of Figures.- List of Tables.- Preface.- Acknowledgments.- Introduction to Operations Management.- Fundamentals of Uncertainty Analysis.- Intuition About Probability.- Discrete Probability Distributions.- Continuous Probability Distributions.- Functions of a Random Variable.- Fundamentals of Optimization.- Basic Inventory Management.- Inventory Management with Uncertain Demand.- Introduction to Linear Programming.- The Transportation Problem.- Assigning Students to Seminars.- Analytic Location Modeling.- Minimizing the Average Distance to a Facility.- A Facility Location Tradeoff.- Fundamentals of Queueing Theory.- A Single-Server Queue.- A More General Single-Server Queue and The Impact of Variability on Queueing Performance.- A Simple Multi-Server Queue.- Solving Queueing Equations Numerically and Simulating the Performance of a Queue.- Decision Theory.- Summary, Where to Next, and Final Thoughts.- Index.- Author's Biography.
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