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

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Detalhes bibliográficos
Resumo: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.
Autores principais:Oliveira,Fabricio
Outros Autores:Hamacher,Silvio
Assunto:supply chain investment planning stochastic optimization stochastic Benders decomposition
Ano:2012
País:Brasil
Tipo de documento:artigo
Tipo de acesso:acesso aberto
Instituição associada:IBICT
Idioma:inglês
Origem:Oasisbr
Descrição
Resumo: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.

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