Stochastic benders decomposition for the supply chain investment planning problem under demand uncertainty

Abstract

This paper presents the application of a stochastic Benders decomposition algorithm for the problem of supply chain investment planning under uncertainty applied to the petroleum byproducts supply chain. The uncertainty considered is related with the unknown demand levels for oil products. For this purpose, a model was developed based on two-stage stochastic programming. It is proposed two different solution methodologies, one based on the classical cutting plane approach presented by Van Slyke & Wets (1969), and other, based on a multi cut extension of it, firstly introduced by Birge & Louveaux (1988). The methods were evaluated on a real sized case study. Preliminary numerical results obtained from computational experiments are encouraging.

Fabricio Oliveira

Associate Professor of Operational Research

Fabricio Oliveira is an Associate Professor of Operational Research in the Department of Mathematics and Systems Analysis.