Adaptive Partition-Based Level Decomposition Methods for Solving Two-Stage Stochastic Programs with Fixed Recourse

Wim van Ackooij (), Welington de Oliveira () and Yongjia Song ()
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Wim van Ackooij: Électricité de France Research & Development, OSIRIS, 91120 Palaiseau, France
Welington de Oliveira: Department of Applied Mathematics, Universidade do Estado do Rio de Janeiro, Rio de Janeiro 20550, Brazil
Yongjia Song: Department of Statistical Sciences and Operations Research, Virginia Commonwealth University, Richmond, Virginia 23284

INFORMS Journal on Computing, 2018, vol. 30, issue 1, 57-70

Abstract: We present a computational study of several strategies to solve two-stage stochastic linear programs by integrating the adaptive partition-based approach with level decomposition. A partition-based formulation is a relaxation of the original stochastic program, obtained by aggregating variables and constraints according to a scenario partition. Partition refinements are guided by the optimal second-stage dual vectors computed at certain first-stage solutions. The proposed approaches rely on the level decomposition with on-demand accuracy to dynamically adjust partitions until an optimal solution is found. Numerical experiments on a large set of test problems including instances with up to one hundred thousand scenarios show the effectiveness of the proposed approaches.

Keywords: stochastic programming; scenario reduction; level decomposition (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (6)

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Persistent link: https://EconPapers.repec.org/RePEc:inm:orijoc:v:30:y:2018:i:1:p:57-70

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