Applications of Stochastic Programming
Applications of Stochastic Programming
William T. Ziemba, University of British Columbia, Vancouver
AUD$260.00
inc GSTThis 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
Product details
June 2005Paperback
9780898715552
184 pages
255 × 178 × 33 mm
1.244kg
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 stochasticsâ„¢ 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.
