Idioma:

A Lagrangean decomposition approach for oil supply chain investment planning under uncertainty with risk considerations

Oliveira, F. ; Gupta, V. ; Hamacher, S. ; Grossmann, I.E.

Computers & chemical engineering, 2013-03, Vol.50, p.184-195 [Periódico revisado por pares]

Kidlington: Elsevier Ltd

Texto completo disponível

Citações Citado por

Enviar para

Título:
A Lagrangean decomposition approach for oil supply chain investment planning under uncertainty with risk considerations
Autor: Oliveira, F. ; Gupta, V. ; Hamacher, S. ; Grossmann, I.E.
Assuntos: Applied sciences ; Economic data ; Energy ; Energy economics ; Exact sciences and technology ; Fossil fuels and derived products ; General, economic and professional studies ; Lagrangean decomposition ; Logistics ; Mechanical engineering. Machine design ; Oil ; Oil and gas ; Operational research and scientific management ; Operational research. Management science ; Portfolio theory ; Risk management ; Scenario decomposition ; Stochastic integer programming ; Supply chain investment planning
É parte de: Computers & chemical engineering, 2013-03, Vol.50, p.184-195
Descrição: ► Planning is addressed for network design/discrete capacity expansion under demand uncertainty. ► A multi-product, multi-period, supply investment planning model is described. ► A two-stage programming model is proposed with alternative non-anticipativity constraints. ► A novel Lagrangean decomposition method is proposed that combines cutting planes and subgradients. We present a scenario decomposition framework based on Lagrangean decomposition for the multi-product, multi-period, supply investment planning problem considering network design and discrete capacity expansion under demand uncertainty. We also consider a risk measure that allows to reduce the probability of incurring in high costs while preserving the decomposable structure of the problem. To solve the resulting large-scale two-stage mixed-integer stochastic linear programming problem we propose a novel Lagrangean decomposition scheme, and compare different formulations for the non-anticipativity conditions. In addition, we present a new hybrid algorithm for updating the Lagrangean multiplier set based on the combination of cutting-plane, subgradient and trust-region strategies. Numerical results suggest that different formulations of the non-anticipativity conditions have a significant impact on the performance of the algorithm. Moreover, we observe that the proposed hybrid approach has superior performance in terms of faster computational times when compared with the traditional subgradient algorithm.
Editor: Kidlington: Elsevier Ltd
Idioma: Inglês

Links

View record in Pascal Francis

Voltar para lista de resultados

Realização: Logos de Redes Sociais:

A Lagrangean decomposition approach for oil supply chain investment planning under uncertainty with risk considerations

Oliveira, F. ; Gupta, V. ; Hamacher, S. ; Grossmann, I.E.

Kidlington: Elsevier Ltd

Buscando em bases de dados remotas. Favor aguardar.