Modeling support for multistage recourse problems

Lecture Notes in Economics and Mathematical Systems

Volumn 532, Issue , 2004, Pages 21-41

  Kall, Peter ^a   Mayer, János ^a  

^a UNIVERSITY OF ZURICH   (Switzerland)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 0344824386     PISSN: 00758442     EISSN: 21969957     Source Type: Book Series    
DOI: 10.1007/978-3-642-55884-9_2     Document Type: Article

References (32)

1. J. R. Birge, M. A. H. Dempster, H. I. Gassmann, E. Gunn, A. J. King, and S. W. Wallace. A standard input format for multiperiod stochastic linear programs. Working Paper WP-87-118, IIASA, Laxenburg, Austria, 1987.
2. J. R. Birge and F. Louveaux. Introduction to stochastic programming. SpringerVerlag, 1997.
3. A. Brooke, D. Kendrick, A. Meeraus, and R. Raman. GAMS. A user's guide. Technical report, GAMS Development Corporation, Washington DC, USA, 1998. It can be downloaded from http://www.gams.com/docs.
4. C. Condevaux-Lanloy and Fragniere E. SETSTOCH: A tool for multistage stochastic programming with recourse. Logilab Technical Report, Dept. of Management Studies, University of Geneva, Switzerland, August 1998.
5. G. Consigli and M. A. H. Dempster. Dynamic stochastic programming for asset-liability management. Ann. Oper. Res., 81:131-161, 1998.
6. M. A. H. Dempster. On stochastic programming II: dynamic problems under risk. Stochastics, 25:14-42, 1988.
7. J. Dupaeova, G. Consigli, and S. W. Wallace. Scenarios for multistage stochastic programs. Ann. Oper. Res., 100:25-53, 2001.
8. J. Dupaeova, N. Growe-Kruska, and W. Romisch. Scenario reduction in stochastic programming: an approach based on probability metrics. Technical report, Stochastic Programming E-Print Series, 2000. http://dochost.rz.huberlin.de/speps.
9. H. I. Gassmann. MSLiP: A computer code for the multistage stochastic linear programming problem. Math. Prog., 47:407-423, 1990.
10. H. I. Gassmann and A. M. Ireland. On the formulation of stochastic linear programs using algebraic modeling languages. Ann. Oper. Res., 64:83-112, 1996.
11. H. I. Gassmann. Modelling support for stochastic programs. Ann. Oper. Res., 82:107-137, 1998.
12. H. I. Gassmann and E. Schweitzer. A comprehensive input format for stochastic linear programs. Ann. Oper. Res., 104:89-125, 2001.
13. J. Gondzio. HOPDM (version 2.12) - A fast LP solver based on a primal-dual interior point method. Eur. J. Oper. Res., 85:221-225, 1995.
14. K. Hoyland, M. Kaut, and S. W. Wallace. A heuristics for generating scenario trees for multistage decision problems. Technical report, Stochastic Programming E-Print Series, 2002. http://dochost.rz.hu-berlin.de/speps.
15. P. Kall and J. Mayer. SLP-IOR: A model management system for stochastic linear programming - system design -. In A.J.M. Beulens and H.-J. Sebastian, editors, Optimization-Based Computer-Aided Modelling and Design, pages 139-157. Springer-Verlag, 1992.
16. P. Kall and J. Mayer. A model management system for stochastic linear programming. In P. Kall, editor, System Modelling and Optimization, pages 580587. Springer-Verlag, 1992.
17. P. Kall and J. Mayer. SLP-IOR: A model management system for stochastic linear programming. In G. Hellwig, P. Kall, and P. Abel, editors, Statistical Methods for Decision Processes, pages 54-63. Daimler Benz AG, StuttgartMohringen, 1994.
18. P. Kall and J. Mayer. Computer support for modeling in stochastic linear programming. In K. Marti and P. Kall, editors, Stochastic Programming: Numerical Techniques and Engineering Applications, pages 54-70. Springer-Verlag, 1995.
19. P. Kall and J. Mayer. SLP-IOR: An interactive model management system for stochastic linear programs. Math. Prog., 75:221-240, 1996.
20. P. Kall and S. W. Wallace. Stochastic programming. John Wiley & Sons, 1994.
21. A. J. King. SP/OSL Version 1.0 Stochastic Programming Interface, User's Guide. IBM Research Division, Thomas J. Watson Research Center, Yorktown Heights, USA, 1994. For the new version 2.0 see IBM Optimization Solutions and Library at http://www-4.ibm.com/software/data/bi/oslj.
22. I. Maros and G. Mitra. Strategies for creating advanced bases for large-scale linear programming problems. INFORMS Journal on Computing, 10(2):248260, Spring 1998.
23. J. Mayer. Stochastic Linear Programming Algorithms: A Comparison Based on a Model Management System. Gordon and Breach, 1998.
24. E. Messina and G. Mitra. Modelling and analysis of multistage stochastic programming problems: A software environment. Eur. J. Oper. Res., 101:343359, 1997.
25. Cs. Meszaros. The augmented system variants of IPM's in two stage stochastic programming. Eur. J. Oper. Res., 101:317-327, 1997.
26. B. A. Murtagh and M. A. Saunders. Large scale linearly constrained optimization. Math. Prog., 14:41-72, 1978.
27. P. Olsen. Multistage stochastic programming with recourse as mathematical programming in an Lp space. SIAM J. Contr. Opt., 14:528-537, 1976.
28. A. Prekopa. Stochastic programming. Kluwer Academic Pub!., 1995.
29. R. T. Rockafellar and R. J.-B. Wets. Nonancipativity and L1-martingales in stochastic optimization problems. Math. Prog. Study, 6:170-187, 1976.
30. R. T. Rockafellar and R. J.-B. Wets. Scenarios and policy aggregation in optimization under uncertainty. Math. Oper. Res., 16:119-147, 1991.
31. W. Romisch and R. Schultz. Multistage integer programs: an introduction. In M. Grotschel, S.O. Krumke, and J. Rambau, editors, Online Optimization of Large Scale Systems, pages 251-271. Springer, 2001.
32. P. Valente, G. Mitra, C. Poojari, and T. Kyriakis. Software tools for stochastic programming: A Stochastic Programming Integrated Environment (SPInE). Technical Report TR/10/01/, Dept. of Mathematical Sciences, Brunei University, UK, 2001.