A heuristic procedure for stochastic integer programs with complete recourse

To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.ejor.2004.09.012 Byline: Guglielmo Lulli (a), Suvrajeet Sen (b) Keywords: Heuristic algorithm; Successive approximation; Stochastic integer programming Abstract: 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. Author Affiliation: (a) Dipartimento di Matematica Pura ed Applicata, Universita di Padova, 35123 Padova, Italy (b) Department of Systems and Industrial Engineering, University of Arizona, Tucson, AZ 85721 USA