Applications of Stochastic Programming
Will be published approx. on 30. June 2005
Book
Paperback/Softback
324 pages
978-0-89871-555-2 (ISBN)
Description
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.
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.
More details
Series
Language
English
Place of publication
New York
United States
Target group
Professional and scholarly
Product notice
Paperback (trade)
Unsewn / adhesive bound
Dimensions
Height: 228 mm
Width: 152 mm
Thickness: 33 mm
Weight
1243 gr
ISBN-13
978-0-89871-555-2 (9780898715552)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Persons
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
Content
Preface: Part I: Stochastic Programming Codes
Chapter 1: Stochastic Programming Computer Implementations, Horand I. Gassmann, SteinW.Wallace, and William T. Ziemba
Chapter 2: The SMPS Format for Stochastic Linear Programs, Horand I. Gassmann
Chapter 3: The IBM Stochastic Programming System, Alan J. King, Stephen E.Wright, Gyana R. Parija, and Robert Entriken
Chapter 4: SQG: Software for Solving Stochastic Programming Problems with Stochastic Quasi-Gradient Methods, Alexei A. Gaivoronski
Chapter 5: Computational Grids for Stochastic Programming, Jeff Linderoth and Stephen J.Wright
Chapter 6: Building and Solving Stochastic Linear Programming Models with SLP-IOR, Peter Kall and Janos Mayer
Chapter 7: Stochastic Programming from Modeling Languages, Emmanuel Fragniere and Jacek Gondzio
Chapter 8: A Stochastic Programming Integrated Environment (SPInE), P. Valente, G. Mitra, and C. A. Poojari
Chapter 9: Stochastic Modelling and Optimization Using Stochastics (TM) , M. A. H. Dempster, J. E. Scott, and G.W. P. Thompson
Chapter 10: An Integrated Modelling Environment for Stochastic Programming, Horand I. Gassmann and David M. Gay
Part II: Stochastic Programming Applications
Chapter 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 Topaloglu
Chapter 13: Modeling Production Planning and Scheduling under Uncertainty, A. Alonso-Ayuso, L. F. Escudero, and M. T. Ortuno
Chapter 14: A Supply Chain Optimization Model for the Norwegian Meat Cooperative, A. Tomasgard and E. Hoeg
Chapter 15: Melt Control: Charge Optimization via Stochastic Programming, Jitka Dupa?cova and Pavel Popela
Chapter 16: A Stochastic Programming Model for Network Resource Utilization in the Presence of Multiclass Demand Uncertainty, Julia L. Higle and Suvrajeet Sen
Chapter 17: Stochastic Optimization and Yacht Racing, A. B. Philpott
Chapter 18: Stochastic Approximation, Momentum, and Nash Play, H. Berglann and S. D. Flam
Chapter 19: Stochastic Optimization for Lake Eutrophication Management, Alan J. King, Laszlo Somlyody, and Roger J.-B.Wets
Chapter 20: Mitigating Anthropogenic Climate Change, GaryW. Yohe
Chapter 21: Groundwater Pollution Control, David W.Watkins, Jr., Daene C. McKinney, and David P. Morton
Chapter 22: Catastrophic Risk Management: Flood and Seismic Risks Case Studies, Tatiana Ermolieva and Yuri Ermoliev
Chapter 23: Refinancing Mortgages in Switzerland, Karl Frauendorfer and Michael Schuerle
Chapter 24. Optimization Models for Structuring Index Funds, Stavros A. Zenios
Chapter 25: Decentralized Risk Management for Global P/C Insurance Companies, John M. Mulvey and Hafize Gaye Erkan
Chapter 26: Wealth Goals Investing, Leonard C. MacLean, Yonggan Zhao, and William T. Ziemba
Chapter 27: Scenario-Based Risk Management Tools, Helmut Mausser and Dan Rosen
Chapter 28: Price Protection Strategies for an Oil Company, E. A. Medova and A. Sembos
Chapter 29: Numerical Comparison of CVaR and CDaR Approaches: Application to Hedge Funds, P. Krokhma, S. Uryasev, and G. Zrazhevsky
Chapter 30: Stochastic Unit Commitment in Hydro-Thermal Power Production Planning, Nicole Groewe-Kuska and Werner Roemisch
Chapter 31: Valuation of Electricity Generation Capacity, Shi-Jie Deng and Shmuel S. Oren
Chapter 32: Stochastic Optimization Problems in Telecommunications, Alexei A. Gaivoronski
Index
Chapter 1: Stochastic Programming Computer Implementations, Horand I. Gassmann, SteinW.Wallace, and William T. Ziemba
Chapter 2: The SMPS Format for Stochastic Linear Programs, Horand I. Gassmann
Chapter 3: The IBM Stochastic Programming System, Alan J. King, Stephen E.Wright, Gyana R. Parija, and Robert Entriken
Chapter 4: SQG: Software for Solving Stochastic Programming Problems with Stochastic Quasi-Gradient Methods, Alexei A. Gaivoronski
Chapter 5: Computational Grids for Stochastic Programming, Jeff Linderoth and Stephen J.Wright
Chapter 6: Building and Solving Stochastic Linear Programming Models with SLP-IOR, Peter Kall and Janos Mayer
Chapter 7: Stochastic Programming from Modeling Languages, Emmanuel Fragniere and Jacek Gondzio
Chapter 8: A Stochastic Programming Integrated Environment (SPInE), P. Valente, G. Mitra, and C. A. Poojari
Chapter 9: Stochastic Modelling and Optimization Using Stochastics (TM) , M. A. H. Dempster, J. E. Scott, and G.W. P. Thompson
Chapter 10: An Integrated Modelling Environment for Stochastic Programming, Horand I. Gassmann and David M. Gay
Part II: Stochastic Programming Applications
Chapter 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 Topaloglu
Chapter 13: Modeling Production Planning and Scheduling under Uncertainty, A. Alonso-Ayuso, L. F. Escudero, and M. T. Ortuno
Chapter 14: A Supply Chain Optimization Model for the Norwegian Meat Cooperative, A. Tomasgard and E. Hoeg
Chapter 15: Melt Control: Charge Optimization via Stochastic Programming, Jitka Dupa?cova and Pavel Popela
Chapter 16: A Stochastic Programming Model for Network Resource Utilization in the Presence of Multiclass Demand Uncertainty, Julia L. Higle and Suvrajeet Sen
Chapter 17: Stochastic Optimization and Yacht Racing, A. B. Philpott
Chapter 18: Stochastic Approximation, Momentum, and Nash Play, H. Berglann and S. D. Flam
Chapter 19: Stochastic Optimization for Lake Eutrophication Management, Alan J. King, Laszlo Somlyody, and Roger J.-B.Wets
Chapter 20: Mitigating Anthropogenic Climate Change, GaryW. Yohe
Chapter 21: Groundwater Pollution Control, David W.Watkins, Jr., Daene C. McKinney, and David P. Morton
Chapter 22: Catastrophic Risk Management: Flood and Seismic Risks Case Studies, Tatiana Ermolieva and Yuri Ermoliev
Chapter 23: Refinancing Mortgages in Switzerland, Karl Frauendorfer and Michael Schuerle
Chapter 24. Optimization Models for Structuring Index Funds, Stavros A. Zenios
Chapter 25: Decentralized Risk Management for Global P/C Insurance Companies, John M. Mulvey and Hafize Gaye Erkan
Chapter 26: Wealth Goals Investing, Leonard C. MacLean, Yonggan Zhao, and William T. Ziemba
Chapter 27: Scenario-Based Risk Management Tools, Helmut Mausser and Dan Rosen
Chapter 28: Price Protection Strategies for an Oil Company, E. A. Medova and A. Sembos
Chapter 29: Numerical Comparison of CVaR and CDaR Approaches: Application to Hedge Funds, P. Krokhma, S. Uryasev, and G. Zrazhevsky
Chapter 30: Stochastic Unit Commitment in Hydro-Thermal Power Production Planning, Nicole Groewe-Kuska and Werner Roemisch
Chapter 31: Valuation of Electricity Generation Capacity, Shi-Jie Deng and Shmuel S. Oren
Chapter 32: Stochastic Optimization Problems in Telecommunications, Alexei A. Gaivoronski
Index