Operations Research Methodologies

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ISBN: 9781420091823 | 1420091824
Cover: Hardcover
Copyright: 11/12/2008

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"As operations research (OR) methodologies continue to grow and flourish in a number decision making fields, a reference that is comprehensive, concise, and easy-to-read is a necessity. This book is a single-source guide to OR techniques, covering fundamental and emerging methodologies in one convenient volume."--BOOK JACKET.

Preface	p. ix
Acknowledgments	p. xi
Editor	p. xiii
Contributors	p. xv
History of Operations Research	p. xvii
Linear Programming	p. 1-1
Brief History of Algorithms for Solving Linear Equations, Linear Inequalities, and LPs	p. 1-1
Applicability of the LP Model: Classical Examples of Direct Applications	p. 1-4
LP Models Involving Transformations of Variables	p. 1-12
Intelligent Modeling Essential to Get Good Results, an Example from Container Shipping	p. 1-18
Planning Uses of LP Models	p. 1-22
Brief Introduction to Algorithms for Solving LP Models	p. 1-26
Software Systems Available for Solving LP Models	p. 1-31
Multiobjective LP Models	p. 1-31
Nonlinear Programming	p. 2-1
Introduction	p. 2-1
Unconstrained Optimization	p. 2-3
Constrained Optimization	p. 2-15
Conclusion	p. 2-19
Integer Programming	p. 3-1
Introduction	p. 3-1
Formulation of IP Models	p. 3-3
Branch and Bound Method	p. 3-7
Cutting Plane Method	p. 3-12
Other Solution Methods and Computer Solution	p. 3-15
Network Optimization	p. 4-1
Introduction	p. 4-1
Notation	p. 4-2
Minimum Cost Flow Problem	p. 4-3
Shortest Path Problem	p. 4-4
Maximum Flow Problem	p. 4-8
Assignment Problem	p. 4-13
Minimum Spanning Tree Problem	p. 4-14
Minimum Cost Multicommodity Flow Problem	p. 4-18
Conclusions	p. 4-19
Multiple Criteria Decision Making	p. 5-1
Some Definitions	p. 5-3
The Concept of "Best Solution"	p. 5-4
Criteria Normalization	p. 5-5
Computing Criteria Weights	p. 5-6
Multiple Criteria Methods for Finite Alternatives	p. 5-8
Multiple Criteria Mathematical Programming Problems	p. 5-15
Goal Programming	p. 5-19
Method of Global Criterion and Compromise Programming	p. 5-27
Interactive Methods	p. 5-29
MCDM Applications	p. 5-34
MCDM Software	p. 5-35
Further Readings	p. 5-35
Decision Analysis	p. 6-1
Introduction	p. 6-1
Terminology for Decision Analysis	p. 6-2
Decision Making under Risk	p. 6-3
Decision Making under Uncertainty	p. 6-17
Practical Decision Analysis	p. 6-21
Conclusions	p. 6-28
Resources	p. 6-29
Dynamic Programming	p. 7-1
Introduction	p. 7-1
Deterministic Dynamic Programming Models	p. 7-3
Stochastic Dynamic Programming Models	p. 7-19
Conclusions	p. 7-24
Stochastic Processes	p. 8-1
Introduction	p. 8-1
Poisson Processes	p. 8-7
Discrete-Time Markov Chains	p. 8-14
Continuous-Time Markov Chains	p. 8-27
Renewal Theory	p. 8-39
Software Products Available for Solving Stochastic Models	p. 8-46
Queueing Theory	p. 9-1
Introduction	p. 9-1
Queueing Theory Basics	p. 9-2
Single-Station and Single-Class Queues	p. 9-8
Single-Station and Multiclass Queues	p. 9-21
Multistation and Single-Class Queues	p. 9-28
Multistation and Multiclass Queues	p. 9-34
Concluding Remarks	p. 9-37
Inventory Control	p. 10-1
Introduction	p. 10-1
Design of Inventory Systems	p. 10-4
Deterministic Inventory Systems	p. 10-9
Stochastic Inventory Systems	p. 10-20
Inventory Control at Multiple Locations	p. 10-27
Inventory Management in Practice	p. 10-34
Conclusions	p. 10-35
Current and Future Research	p. 10-36
Complexity and Large-Scale Networks	p. 11-1
Introduction	p. 11-1
Statistical Properties of Complex Networks	p. 11-6
Modeling of Complex Networks	p. 11-11
Why "Complex" Networks	p. 11-16
Optimization in Complex Networks	p. 11-18
Conclusions	p. 11-26
Simulation	p. 12-1
Introduction	p. 12-1
Basics of Simulation	p. 12-3
Simulation Languages and Software	p. 12-15
Simulation Projects-The Bigger Picture	p. 12-20
Summary	p. 12-22
Metaheuristics for Discrete Optimization Problems	p. 13-1
Mathematical Framework for Single Solution Metaheuristics	p. 13-3
Network Location Problems	p. 13-3
Multistart Local Search	p. 13-5
Simulated Annealing	p. 13-6
Plain Vanilla Tabu Search	p. 13-8
Active Structural Acoustic Control (ASAC)	p. 13-10
Nature Reserve Site Selection	p. 13-13
Damper Placement in Flexible Truss Structures	p. 13-21
Reactive Tabu Search	p. 13-29
Discussion	p. 13-35
Robust Optimization	p. 14-1
Introduction	p. 14-1
Classical Models	p. 14-2
Robust Optimization Models	p. 14-10
More Applications	p. 14-16
Summary	p. 14-30
Index	p. I-1
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