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Lagrangean decomposition for large-scale two-stage stochastic mixed 0-1 problems

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  • Escudero Bueno, Laureano F.
  • Garín Martín, María Araceli
  • Pérez Sainz de Rozas, Gloria
  • Unzueta Inchaurbe, Aitziber

Abstract

In this paper we study solution methods for solving the dual problem corresponding to the Lagrangean Decomposition of two stage stochastic mixed 0-1 models. We represent the two stage stochastic mixed 0-1 problem by a splitting variable representation of the deterministic equivalent model, where 0-1 and continuous variables appear at any stage. Lagrangean Decomposition is proposed for satisfying both the integrality constraints for the 0-1 variables and the non-anticipativity constraints. We compare the performance of four iterative algorithms based on dual Lagrangean Decomposition schemes, as the Subgradient method, the Volume algorithm, the Progressive Hedging algorithm and the Dynamic Constrained Cutting Plane scheme. We test the conditions and properties of convergence for medium and large-scale dimension stochastic problems. Computational results are reported.

Suggested Citation

  • Escudero Bueno, Laureano F. & Garín Martín, María Araceli & Pérez Sainz de Rozas, Gloria & Unzueta Inchaurbe, Aitziber, 2010. "Lagrangean decomposition for large-scale two-stage stochastic mixed 0-1 problems," BILTOKI 1134-8984, Universidad del País Vasco - Departamento de Economía Aplicada III (Econometría y Estadística).
    • Handle: RePEc:ehu:biltok:5566
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    References listed on IDEAS

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