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Applications of Stochastic Programming

Applications of Stochastic Programming

£87.00

Part of MPS-SIAM Series on Optimization

  • Date Published: June 2005
  • availability: This item is not supplied by Cambridge University Press in your region. Please contact Soc for Industrial & Applied Mathematics for availability.
  • format: Paperback
  • isbn: 9780898715552

£ 87.00
Paperback

This item is not supplied by Cambridge University Press in your region. Please contact Soc for Industrial & Applied Mathematics for availability.
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About the Authors
  • This is the first book devoted to the full scale of applications of stochastic programming, and to provide access to publicly available algorithmic systems. The 32 contributed papers are written by leading stochastic programming specialists and reflect the recent advanced research on algorithms and applications. The book consists of two parts: the first 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 wanting to make models without extensive programming and other implementation costs. 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.

    • First book devoted to full scale applications of stochastic programming
    • Provides access to publicly available algorithmic systems
    • Contributions from leading specialists in stochastic programming
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    Product details

    • Date Published: June 2005
    • format: Paperback
    • isbn: 9780898715552
    • length: 184 pages
    • dimensions: 255 x 178 x 33 mm
    • weight: 1.244kg
    • availability: This item is not supplied by Cambridge University Press in your region. Please contact Soc for Industrial & Applied Mathematics for availability.
  • Table of Contents

    Preface
    Part I. Stochastic Programming Codes:
    1. Stochastic programming computer implementations Horand I. Gassmann, SteinW.Wallace and William T. Ziemba
    2. The SMPS format for stochastic linear programs Horand I. Gassmann
    3. The IBM stochastic programming system Alan J. King, Stephen E. Wright, Gyana R. Parija and Robert Entriken
    4. SQG: software for solving stochastic programming problems with stochastic quasi-gradient methods Alexei A. Gaivoronski
    5. Computational grids for stochastic programming Jeff Linderoth and Stephen J. Wright
    6. Building and solving stochastic linear programming models with SLP-IOR Peter Kall and János Mayer
    7. Stochastic programming from modeling languages Emmanuel Fragnière and Jacek Gondzio
    8. A stochastic programming integrated environment (SPInE) P. Valente, G. Mitra, and C. A. Poojari
    9. Stochastic modelling and optimization using stochastics™ M. A. H. Dempster, J. E. Scott and G. W. P. Thompson
    10. An integrated modelling environment for stochastic programming Horand I. Gassmann and David M. Gay
    Part II. Stochastic Programming Applications:
    11. Introduction to stochastic programming applications Horand I. Gassmann, Sandra L. Schwartz, SteinW. Wallace, and William T. Ziemba 12. Fleet management Warren B. Powell and Huseyin Topaloglu
    13. Modeling production planning and scheduling under uncertainty A. Alonso-Ayuso, L. F. Escudero and M. T. Ortuño
    14. A supply chain optimization model for the Norwegian meat cooperative A. Tomasgard and E. Høeg
    15. Melt control: charge optimization via stochastic programming Jitka Dupacová and Pavel Popela
    16. A stochastic programming model for network resource utilization in the presence of multiclass demand uncertainty Julia L. Higle and Suvrajeet Sen
    17. Stochastic optimization and yacht racing A. B. Philpott
    18. Stochastic approximation, momentum, and Nash play H. Berglann and S. D. Flåm
    19. Stochastic optimization for lake eutrophication management Alan J. King, László Somlyódy and Roger J.-B. Wets
    20. Mitigating anthropogenic climate change Gary W. Yohe
    21. Groundwater pollution control David W. Watkins, Jr., Daene C. McKinney and David P. Morton
    22. Catastrophic risk management: flood and seismic risks case studies Tatiana Ermolieva and Yuri Ermoliev
    23. Refinancing mortgages in Switzerland Karl Frauendorfer and Michael Schürle
    24. Optimization models for structuring index funds Stavros A. Zenios
    25. Decentralized risk management for global P/C insurance companies John M. Mulvey and Hafize Gaye Erkan
    26. Wealth goals investing Leonard C. MacLean, Yonggan Zhao and William T. Ziemba
    27. Scenario-based risk management tools Helmut Mausser and Dan Rosen
    28. Price protection strategies for an oil company E. A. Medova and A. Sembos
    29. Numerical comparison of CVaR and CDaR approaches: application to hedge funds P. Krokhma, S. Uryasev, and G. Zrazhevsky
    30. Stochastic unit commitment in hydro-thermal power production planning Nicole Gröwe-Kuska and Werner Römisch
    31. Valuation of electricity generation capacity Shi-Jie Deng and Shmuel S. Oren
    32. Stochastic optimization problems in telecommunications Alexei A. Gaivoronski
    Index.

  • Editors

    Stein W. Wallace, Molde University College, Norway

    William T. Ziemba, University of British Columbia, Vancouver

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