TY - JOUR

T1 - A heuristic procedure for stochastic integer programs with complete recourse

AU - Lulli, Guglielmo

AU - Sen, Suvrajeet

PY - 2006/6/16

Y1 - 2006/6/16

N2 - In this paper, we propose a successive approximation heuristic which solves large stochastic mixed-integer programming problem with complete fixed recourse. We refer to this method as the Scenario Updating Method, since it solves the problem by considering only a subset of scenarios which is updated at each iteration. Only those scenarios which imply a significant change in the objective function are added. The algorithm is terminated when no such scenarios are available to enter in the current scenario subtree. Several rules to select scenarios are discussed. Bounds on heuristic solutions are computed by relaxing some of the non-anticipativity constraints. The proposed procedure is tested on a multistage stochastic batch-sizing problem.

AB - In this paper, we propose a successive approximation heuristic which solves large stochastic mixed-integer programming problem with complete fixed recourse. We refer to this method as the Scenario Updating Method, since it solves the problem by considering only a subset of scenarios which is updated at each iteration. Only those scenarios which imply a significant change in the objective function are added. The algorithm is terminated when no such scenarios are available to enter in the current scenario subtree. Several rules to select scenarios are discussed. Bounds on heuristic solutions are computed by relaxing some of the non-anticipativity constraints. The proposed procedure is tested on a multistage stochastic batch-sizing problem.

KW - Heuristic algorithm

KW - Stochastic integer programming

KW - Successive approximation

U2 - 10.1016/j.ejor.2004.09.012

DO - 10.1016/j.ejor.2004.09.012

M3 - Journal article

AN - SCOPUS:31144475808

VL - 171

SP - 879

EP - 890

JO - European Journal of Operational Research

JF - European Journal of Operational Research

SN - 0377-2217

IS - 3

ER -