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An Adaptive Partition-based Level Decomposition for Solving Two-stage Stochastic Programs with Fixed Recourse

Wim van Ackooij(wim.van.ackooij***at***gmail.com)
Welington de Oliveira(welington***at***ime.uerj.br)
Yongjia Song(ysong3***at***vcu.edu)

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

Category 1: Stochastic Programming

Citation: Submitted for publication

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Entry Submitted: 03/16/2016
Entry Accepted: 03/17/2016
Entry Last Modified: 03/16/2016

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