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

Research output: Contribution to journalArticle


Research units

  • Pontifícia Universidade Católica do Rio de Janeiro


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.


Original languageEnglish
Pages (from-to)663-676
Number of pages14
JournalPesquisa Operacional
Issue number3
Publication statusPublished - Sep 2012
MoE publication typeA1 Journal article-refereed

    Research areas

  • Stochastic benders decomposition, Stochastic optimization, Supply chain investment planning

ID: 16007931