Decomposition of Multistage Stochastic Programs with Recombining Scenraio Trees

This paper presents a decomposition approach for linear multistage stochastic programs, that is based on the concept of recombining scenario trees. The latter, widely applied in Mathematical Finance, may prevent the node number of the scenario tree to grow exponentially with the number of time stages. It is shown how this property may be exploited within a non-Markovian framework and under time-coupling constraints. Being close to the well-established Nested Benders Decomposition, our approach uses the special structure of recombining trees for simultaneous cutting plane approximations. Convergence is proved and stopping criteria are deduced. Techniques for the generation of suitable scenario trees and some numerical examples are presented.

[1]  Peter Kall,et al.  Stochastic Programming , 1995 .

[2]  Werner Römisch,et al.  Stability of Multistage Stochastic Programs , 2006, SIAM J. Optim..

[3]  George L. Nemhauser,et al.  Handbooks in operations research and management science , 1989 .

[4]  Hanif D. Sherali,et al.  Decomposition with branch-and-cut approaches for two-stage stochastic mixed-integer programming , 2006, Math. Program..

[5]  G. Pagès,et al.  A QUANTIZATION TREE METHOD FOR PRICING AND HEDGING MULTIDIMENSIONAL AMERICAN OPTIONS , 2005 .

[6]  Jitka Dupacová,et al.  Scenarios for Multistage Stochastic Programs , 2000, Ann. Oper. Res..

[7]  Lennart Söder,et al.  Fluctuations and predictability of wind and hydropower. Deliverable 2.1 , 2004 .

[8]  S. Ross,et al.  Option pricing: A simplified approach☆ , 1979 .

[9]  Dag Haugland,et al.  Solving many linear programs that differ only in the righthand side , 1988 .

[10]  Suresh P. Sethi,et al.  A theory of rolling horizon decision making , 1991, Ann. Oper. Res..

[11]  Horand I. Gassmann,et al.  Mslip: A computer code for the multistage stochastic linear programming problem , 1990, Math. Program..

[12]  John R. Birge,et al.  Decomposition and Partitioning Methods for Multistage Stochastic Linear Programs , 1985, Oper. Res..

[13]  Jamie B. Kruse,et al.  Time series analysis of wind speed with time‐varying turbulence , 2006 .

[14]  R. Wets,et al.  L-SHAPED LINEAR PROGRAMS WITH APPLICATIONS TO OPTIMAL CONTROL AND STOCHASTIC PROGRAMMING. , 1969 .

[15]  Allen Gersho,et al.  Vector quantization and signal compression , 1991, The Kluwer international series in engineering and computer science.

[16]  M. Dempster Sequential Importance Sampling Algorithms for Dynamic Stochastic Programming , 2006 .

[17]  Suvrajeet Sen,et al.  The Scenario Generation Algorithm for Multistage Stochastic Linear Programming , 2005, Math. Oper. Res..

[18]  Rüdiger Schultz,et al.  Stochastic programming with integer variables , 2003, Math. Program..

[19]  Jitka Dupacová,et al.  Scenario reduction in stochastic programming , 2003, Math. Program..

[20]  S. Graf,et al.  Foundations of Quantization for Probability Distributions , 2000 .

[21]  Georg Ch. Pflug,et al.  Scenario tree generation for multiperiod financial optimization by optimal discretization , 2001, Math. Program..

[22]  N. Growe-Kuska,et al.  Scenario reduction and scenario tree construction for power management problems , 2003, 2003 IEEE Bologna Power Tech Conference Proceedings,.

[23]  Georg Ch. Pflug,et al.  Tree Approximations of Dynamic Stochastic Programs , 2007, SIAM J. Optim..

[24]  W. Römisch,et al.  Scenario tree modelling for multistage stochastic programs , 2006 .

[25]  David S. Johnson,et al.  Computers and Intractability: A Guide to the Theory of NP-Completeness , 1978 .

[26]  R. Wets Solving stochastic programs with simple recourse , 1983 .

[27]  John M. Wilson,et al.  Introduction to Stochastic Programming , 1998, J. Oper. Res. Soc..

[28]  Julia L. Higle,et al.  The C 3 theorem and a D 2 algorithm for large scale stochastic integer programming , 2000 .