Operations research and management science handbook

Başlık:

Yazar:

Ravindran, A., 1944-

ISBN:

9780849397219

Yayım Bilgisi:

Boca Raton : CRC Press, c2008.

Fiziksel Tanım:

1 v. (various pagings) : ill., maps ; 27 cm.

Series:

The operations research series

Series Title:

The operations research series

Konu Terimleri:

Yöneylem araştırması -- El kitapları, vb.

Operations research -- Handbooks, manuals, etc.

Added Author:

Ravindran, A., 1944-

Mevcut:*

Library	Materyal Türü	Barkod	Yer Numarası	Durum
Searching... Pamukkale Merkez Kütüphanesi	Kitap	0055388	T57.6O6446 2008	Searching... Unknown

Operations Research (OR) began as an interdisciplinary activity to solve complex military problems during World War II. Utilizing principles from mathematics, engineering, business, computer science, economics, and statistics, OR has developed into a full fledged academic discipline with practical application in business, industry, government and military. Currently regarded as a body of established mathematical models and methods essential to solving complicated management issues, OR provides quantitative analysis of problems from which managers can make objective decisions. Operations Research and Management Science (OR/MS) methodologies continue to flourish in numerous decision making fields.

Featuring a mix of international authors, Operations Research and Management Science Handbook combines OR/MS models, methods, and applications into one comprehensive, yet concise volume. The first resource to reach for when confronting OR/MS difficulties, this text -

Provides a single source guide in OR/MS Bridges theory and practice Covers all topics relevant to OR/MS Offers a quick reference guide for students, researchers and practitioners Contains unified and up-to-date coverage designed and edited with non-experts in mind Discusses software availability for all OR/MS techniques Includes contributions from a mix of domestic and international experts

The 26 chapters in the handbook are divided into two parts. Part I contains 14 chapters that cover the fundamental OR/MS models and methods. Each chapter gives an overview of a particular OR/MS model, its solution methods and illustrates successful applications. Part II of the handbook contains 11 chapters discussing the OR/MS applications in specific areas. They include airlines, e-commerce, energy systems, finance, military, production systems, project management, quality control, reliability, supply chain management and water resources. Part

II ends with a chapter on the future of OR/MS applications.

Katta G. MurtyTheodore B. Trafalis and Robin C. GilbertMichael WengMehmet Bayram YildirimAbu S. M. Masud and A. Ravi RavindranCerry M. KleinJose A. VenturaSusan H. XuNatarajan GautamFarhad Azadivar and Atul RangarajanHari P. Thadakamalla and Soundar R. T. Kumara and Reka AlbertCatherine M. HarmonoskyRex K. KincaidH. J. Greenberg and Tod MorrisonAdedeji B. BadiruQianmei Feng and Kailash C. KapurLawrence M. LeemisBobbie L. Foote and Katta G. MurtyC. Randy Hudson and Adedeji B. BadiruJane L. Snowdon and Giuseppe PaleologoAliza R. Heching and Alan J. KingDonald P. WarsingSowmyanarayanan SadagopanG.V. LoganathanJeffery D. Weir and Marlin U. ThomasP. Balasubramanian

Preface	p. xiii
Acknowledgments	p. xv
Editor	p. xvii
Contributors	p. xix
History of Operations Research and Management Science	p. xxi
I OR/MS Models and Methods
1 Linear Programming	p. 1-1
1.1 Brief History of Algorithms for Solving Linear Equations, Linear Inequalities, and LPs	p. 1-1
1.2 Applicability of the LP Model: Classical Examples of Direct Applications	p. 1-4
1.3 LP Models Involving Transformations of Variables	p. 1-12
1.4 Intelligent Modeling Essential to Get Good Results, an Example from Container Shipping	p. 1-18
1.5 Planning Uses of LP Models	p. 1-22
1.6 Brief Introduction to Algorithms for Solving LP Models	p. 1-26
1.7 Software Systems Available for Solving LP Models	p. 1-31
1.8 Multiobjective LP Models	p. 1-31
2 Nonlinear Programming	p. 2-1
2.1 Introduction	p. 2-1
2.2 Unconstrained Optimization	p. 2-3
2.3 Constrained Optimization	p. 2-15
2.4 Conclusion	p. 2-19
3 Integer Programming	p. 3-1
3.1 Introduction	p. 3-1
3.2 Formulation of IP Models	p. 3-3
3.3 Branch and Bound Method	p. 3-7
3.4 Cutting Plane Method	p. 3-12
3.5 Other Solution Methods and Computer Solution	p. 3-15
4 Network Optimization	p. 4-1
4.1 Introduction	p. 4-1
4.2 Notation	p. 4-2
4.3 Minimum Cost Flow Problem	p. 4-3
4.4 Shortest Path Problem	p. 4-4
4.5 Maximum Flow Problem	p. 4-8
4.6 Assignment Problem	p. 4-13
4.7 Minimum Spanning Tree Problem	p. 4-14
4.8 Minimum Cost Multicommodity Flow Problem	p. 4-18
4.9 Conclusions	p. 4-19
5 Multiple Criteria Decision Making	p. 5-1
5.1 Some Definitions	p. 5-3
5.2 The Concept of "Best Solution"	p. 5-4
5.3 Criteria Normalization	p. 5-5
5.4 Computing Criteria Weights	p. 5-6
5.5 Multiple Criteria Methods for Finite Alternatives	p. 5-8
5.6 Multiple Criteria Mathematical Programming Problems	p. 5-15
5.7 Goal Programming	p. 5-19
5.8 Method of Global Criterion and Compromise Programming	p. 5-27
5.9 Interactive Methods	p. 5-29
5.10 MCDM Applications	p. 5-34
5.11 MCDM Software	p. 5-35
5.12 Further Readings	p. 5-35
6 Decision Analysis	p. 6-1
6.1 Introduction	p. 6-1
6.2 Terminology for Decision Analysis	p. 6-2
6.3 Decision Making under Risk	p. 6-3
6.4 Decision Making under Uncertainty	p. 6-17
6.5 Practical Decision Analysis	p. 6-21
6.6 Conclusions	p. 6-28
6.7 Resources	p. 6-29
7 Dynamic Programming	p. 7-1
7.1 Introduction	p. 7-1
7.2 Deterministic Dynamic Programming Models	p. 7-3
7.3 Stochastic Dynamic Programming Models	p. 7-19
7.4 Conclusions	p. 7-24
8 Stochastic Processes	p. 8-1
8.1 Introduction	p. 8-1
8.2 Poisson Processes	p. 8-7
8.3 Discrete-Time Markov Chains	p. 8-14
8.4 Continuous-Time Markov Chains	p. 8-27
8.5 Renewal Theory	p. 8-39
8.6 Software Products Available for Solving Stochastic Models	p. 8-46
9 Queueing Theory	p. 9-1
9.1 Introduction	p. 9-1
9.2 Queueing Theory Basics	p. 9-2
9.3 Single-Station and Single-Class Queues	p. 9-8
9.4 Single-Station and Multiclass Queues	p. 9-21
9.5 Multistation and Single-Class Queues	p. 9-28
9.6 Multistation and Multiclass Queues	p. 9-34
9.7 Concluding Remarks	p. 9-37
10 Inventory Control	p. 10-1
10.1 Introduction	p. 10-1
10.2 Design of Inventory Systems	p. 10-4
10.3 Deterministic Inventory Systems	p. 10-9
10.4 Stochastic Inventory Systems	p. 10-20
10.5 Inventory Control at Multiple Locations	p. 10-27
10.6 Inventory Management in Practice	p. 10-34
10.7 Conclusions	p. 10-35
10.8 Current and Future Research	p. 10-36
11 Complexity and Large-Scale Networks	p. 11-1
11.1 Introduction	p. 11-1
11.2 Statistical Properties of Complex Networks	p. 11-6
11.3 Modeling of Complex Networks	p. 11-11
11.4 Why "Complex" Networks	p. 11-16
11.5 Optimization in Complex Networks	p. 11-18
11.6 Conclusions	p. 11-26
12 Simulation	p. 12-1
12.1 Introduction	p. 12-1
12.2 Basics of Simulation	p. 12-3
12.3 Simulation Languages and Software	p. 12-15
12.4 Simulation Projects-The Bigger Picture	p. 12-20
12.5 Summary	p. 12-22
13 Metaheuristics for Discrete Optimization Problems	p. 13-1
13.1 Mathematical Framework for Single Solution Metaheuristics	p. 13-3
13.2 Network Location Problems	p. 13-3
13.3 Multistart Local Search	p. 13-5
13.4 Simulated Annealing	p. 13-6
13.5 Plain Vanilla Tabu Search	p. 13-8
13.6 Active Structural Acoustic Control (ASAC)	p. 13-10
13.7 Nature Reserve Site Selection	p. 13-13
13.8 Damper Placement in Flexible Truss Structures	p. 13-21
13.9 Reactive Tabu Search	p. 13-29
13.10 Discussion	p. 13-35
14 Robust Optimization	p. 14-1
14.1 Introduction	p. 14-1
14.2 Classical Models	p. 14-2
14.3 Robust Optimization Models	p. 14-10
14.4 More Applications	p. 14-16
14.5 Summary	p. 14-30
II OR/MS Applications
15 Project Management	p. 15-1
15.1 Introduction	p. 15-1
15.2 Critical Path Method	p. 15-3
15.3 PERT Network Analysis	p. 15-18
15.4 Statistical Analysis of Project Duration	p. 15-23
15.5 Precedence Diagramming Method	p. 15-26
15.6 Software Tools for Project Management	p. 15-34
15.7 Conclusion	p. 15-37
16 Quality Control	p. 16-1
16.1 Introduction	p. 16-1
16.2 Quality Control and Product Life Cycle	p. 16-2
16.3 New Trends and Relationship to Six Sigma	p. 16-5
16.4 Statistical Process Control	p. 16-7
16.5 Process Capability Studies	p. 16-16
16.6 Advanced Control Charts	p. 16-18
16.7 Limitations of Acceptance Sampling	p. 16-20
16.8 Conclusions	p. 16-20
17 Reliability	p. 17-1
17.1 Introduction	p. 17-1
17.2 Reliability in System Design	p. 17-3
17.3 Lifetime Distributions	p. 17-10
17.4 Parametric Models	p. 17-17
17.5 Parameter Estimation in Survival Analysis	p. 17-22
17.6 Nonparametric Methods	p. 17-32
17.7 Assessing Model Adequacy	p. 17-36
17.8 Summary	p. 17-40
18 Production Systems	p. 18-1
18.1 Production Planning Problem	p. 18-1
18.2 Demand Forecasting	p. 18-2
18.3 Models for Production Layout Design	p. 18-12
18.4 Scheduling of Production and Service Systems	p. 18-20
19 Energy Systems	p. 19-1
19.1 Introduction	p. 19-1
19.2 Definition of Energy	p. 19-2
19.3 Harnessing Natural Energy	p. 19-3
19.4 Mathematical Modeling of Energy Systems	p. 19-3
19.5 Linear Programming Model of Energy Resource Combination	p. 19-4
19.6 Integer Programming Model for Energy Investment Options	p. 19-5
19.7 Simulation and Optimization of Distributed Energy Systems	p. 19-11
19.8 Point-of-Use Energy Generation	p. 19-11
19.9 Modeling of CHP Systems	p. 19-12
19.10 Economic Optimization Methods	p. 19-13
19.11 Design of a Model for Optimization of CHP System Capacities	p. 19-16
19.12 Capacity Optimization	p. 19-21
19.13 Implementation of the Computer Model	p. 19-24
19.14 Other Scenarios	p. 19-27
20 Airline Optimization	p. 20-1
20.1 Introduction	p. 20-1
20.2 Schedule Planning	p. 20-5
20.3 Revenue Management	p. 20-14
20.4 Aircraft Load Planning	p. 20-21
20.5 Future Research Directions and Conclusions	p. 20-23
21 Financial Engineering	p. 21-1
21.1 Introduction	p. 21-1
21.2 Return	p. 21-3
21.3 Estimating an Asset's Mean and Variance	p. 21-4
21.4 Diversification	p. 21-6
21.5 Efficient Frontier	p. 21-8
21.6 Utility Analysis	p. 21-10
21.7 Black-Litterman Asset Allocation Model	p. 21-13
21.8 Risk Management	p. 21-18
21.9 Options	p. 21-22
21.10 Valuing Options	p. 21-24
21.11 Dynamic Programming	p. 21-28
21.12 Pricing American Options Using Dynamic Programming	p. 21-29
21.13 Comparison of Monte Carlo Simulation and Dynamic Programming	p. 21-33
21.14 Multi-Period Asset Liability Management	p. 21-33
21.15 Conclusions	p. 21-36
22 Supply Chain Management	p. 22-1
22.1 Introduction	p. 22-1
22.2 Managing Inventories in the Supply Chain	p. 22-6
22.3 Managing Transportation in the Supply Chain	p. 22-24
22.4 Managing Locations in the Supply Chain	p. 22-38
22.5 Managing Dyads in the Supply Chain	p. 22-48
22.6 Discussion and Conclusions	p. 22-58
23 E-Commerce	p. 23-1
23.1 Introduction	p. 23-1
23.2 Evolution of E-Commerce	p. 23-3
23.3 OR/MS and E-Commerce	p. 23-5
23.4 OR Applications in E-Commerce	p. 23-7
23.5 Tools-Applications Matrix	p. 23-20
23.6 Way Forward	p. 23-21
23.7 Summary	p. 23-21
24 Water Resources	p. 24-1
24.1 Introduction	p. 24-1
24.2 Optimal Operating Policy for Reservoir Systems	p. 24-4
24.3 Water Distribution Systems Optimization	p. 24-10
24.4 Preferences in Choosing Domestic Plumbing Materials	p. 24-18
24.5 Stormwater Management	p. 24-21
24.6 Groundwater Management	p. 24-23
24.7 Summary	p. 24-25
25 Military Applications	p. 25-1
25.1 Introduction	p. 25-1
25.2 Background on Military OR	p. 25-2
25.3 Current Military Applications of OR	p. 25-3
25.4 Concluding Remarks	p. 25-10
26 Future of OR/MS Applications: A Practitioner's Perspective	p. 26-1
26.1 Past as a Guide to the Future	p. 26-2
26.2 Impact of the Internet	p. 26-6
26.3 Emerging Opportunities	p. 26-8
Index	p. I-1

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