Journal article

Proximity Benders: a decomposition heuristic for stochastic programs

N Boland, M Fischetti, M Monaci, M Savelsbergh

Journal of Heuristics | Published : 2016

Abstract

In this paper we present a heuristic approach to two-stage mixed-integer linear stochastic programming models with continuous second stage variables. A common solution approach for these models is Benders decomposition, in which a sequence of (possibly infeasible) solutions is generated, until an optimal solution is eventually found and the method terminates. As convergence may require a large amount of computing time for hard instances, the method may be unsatisfactory from a heuristic point of view. Proximity search is a recently-proposed heuristic paradigm in which the problem at hand is modified and iteratively solved with the aim of producing a sequence of improving feasible solutions. ..

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University of Melbourne Researchers

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