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Applications of Stochastic Programming

Häftad, Engelska, 2005

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Research on algorithms and applications of stochastic programming, the study of procedures for decision making under uncertainty over time, has been very active in recent years and deserves to be more widely known. This is the first book devoted to the full scale of applications of stochastic programming and also the first to provide access to publicly available algorithmic systems. The 32 contributed papers in this volume are written by leading stochastic programming specialists and reflect the high level of activity in recent years in research on algorithms and applications. The book introduces the power of stochastic programming to a wider audience and demonstrates the application areas where this approach is superior to other modeling approaches.Applications of Stochastic Programming consists of two parts. The first part presents papers describing publicly available stochastic programming systems that are currently operational. All the codes have been extensively tested and developed and will appeal to researchers and developers who want to make models without extensive programming and other implementation costs. The codes are a synopsis of the best systems available, with the requirement that they be user-friendly, ready to go, and publicly available.The second part of the book is a diverse collection of application papers in areas such as production, supply chain and scheduling, gaming, environmental and pollution control, financial modeling, telecommunications, and electricity. It contains the most complete collection of real applications using stochastic programming available in the literature. The papers show how leading researchers choose to treat randomness when making planning models, with an emphasis on modeling, data, and solution approaches.

Produktinformation

Utgivningsdatum2005-06-30
Mått152 x 229 x 33 mm
Vikt1 256 g
FormatHäftad
SpråkEngelska
SerieMOS-SIAM Series on Optimization
Antal sidor324
FörlagSociety for Industrial & Applied Mathematics,U.S.
ISBN9780898715552

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Stein W. Wallace is Professor of Quantitative Logistics at Molde University College, Norway. He has held visiting positions at institutions in both Europe and the United States. He is co-author, with Peter Kall of Zurich, of the first textbook in stochastic programming, and he has published more than 50 articles in refereed journals. William T. Ziemba is Alumni Professor of Financial Modeling and Stochastic Optimization at the Sauder School of Business at the University of British Columbia. He has held visiting positions at universities in Europe, the United States, and Asia and is a consultant in the financial and investment industries. He has served as CORS editor of INFOR and department of finance editor of Management Science. He is author or editor of over 20 books and has published over 200 papers in refereed journals

Preface: Part I: Stochastic Programming CodesChapter 1: Stochastic Programming Computer Implementations, Horand I. Gassmann, SteinW.Wallace, and William T. ZiembaChapter 2: The SMPS Format for Stochastic Linear Programs, Horand I. GassmannChapter 3: The IBM Stochastic Programming System, Alan J. King, Stephen E.Wright, Gyana R. Parija, and Robert EntrikenChapter 4: SQG: Software for Solving Stochastic Programming Problems with Stochastic Quasi-Gradient Methods, Alexei A. GaivoronskiChapter 5: Computational Grids for Stochastic Programming, Jeff Linderoth and Stephen J.WrightChapter 6: Building and Solving Stochastic Linear Programming Models with SLP-IOR, Peter Kall and János MayerChapter 7: Stochastic Programming from Modeling Languages, Emmanuel Fragnière and Jacek GondzioChapter 8: A Stochastic Programming Integrated Environment (SPInE), P. Valente, G. Mitra, and C. A. PoojariChapter 9: Stochastic Modelling and Optimization Using Stochastics™ , M. A. H. Dempster, J. E. Scott, and G.W. P. ThompsonChapter 10: An Integrated Modelling Environment for Stochastic Programming, Horand I. Gassmann and David M. GayPart II: Stochastic Programming ApplicationsChapter 11: Introduction to Stochastic Programming Applications Horand I. Gassmann, Sandra L. Schwartz, SteinW.Wallace, and William T. Ziemba Chapter 12: Fleet Management, Warren B. Powell and Huseyin TopalogluChapter 13: Modeling Production Planning and Scheduling under Uncertainty, A. Alonso-Ayuso, L. F. Escudero, and M. T. OrtuñoChapter 14: A Supply Chain Optimization Model for the Norwegian Meat Cooperative, A. Tomasgard and E. HøegChapter 15: Melt Control: Charge Optimization via Stochastic Programming, Jitka Dupa?cová and Pavel PopelaChapter 16: A Stochastic Programming Model for Network Resource Utilization in the Presence of Multiclass Demand Uncertainty, Julia L. Higle and Suvrajeet SenChapter 17: Stochastic Optimization and Yacht Racing, A. B. PhilpottChapter 18: Stochastic Approximation, Momentum, and Nash Play, H. Berglann and S. D. FlåmChapter 19: Stochastic Optimization for Lake Eutrophication Management, Alan J. King, László Somlyódy, and Roger J.-B.WetsChapter 20: Mitigating Anthropogenic Climate Change, GaryW. YoheChapter 21: Groundwater Pollution Control, David W.Watkins, Jr., Daene C. McKinney, and David P. MortonChapter 22: Catastrophic Risk Management: Flood and Seismic Risks Case Studies, Tatiana Ermolieva and Yuri ErmolievChapter 23: Refinancing Mortgages in Switzerland, Karl Frauendorfer and Michael SchürleChapter 24. Optimization Models for Structuring Index Funds, Stavros A. ZeniosChapter 25: Decentralized Risk Management for Global P/C Insurance Companies, John M. Mulvey and Hafize Gaye ErkanChapter 26: Wealth Goals Investing, Leonard C. MacLean, Yonggan Zhao, and William T. ZiembaChapter 27: Scenario-Based Risk Management Tools, Helmut Mausser and Dan RosenChapter 28: Price Protection Strategies for an Oil Company, E. A. Medova and A. SembosChapter 29: Numerical Comparison of CVaR and CDaR Approaches: Application to Hedge Funds, P. Krokhma, S. Uryasev, and G. ZrazhevskyChapter 30: Stochastic Unit Commitment in Hydro-Thermal Power Production Planning, Nicole Gröwe-Kuska and Werner RömischChapter 31: Valuation of Electricity Generation Capacity, Shi-Jie Deng and Shmuel S. OrenChapter 32: Stochastic Optimization Problems in Telecommunications, Alexei A. GaivoronskiIndex