A general algorithm for solving two-stage stochastic mixed 0-1 first-stage problems

Authors:
L. F. Escudero;M. A. Garín;M. Merino;G. Pérez
Affiliations:
Dpto. de Estadística e Investigación Operativa, Universidad Rey Juan Carlos, Móstoles, Madrid, Spain;Dpto. de Economía Aplicada III, Fac. CC. Económicas y Empresariares, UPV/EHU, Universidad del País Vasco, Avd. Lehendakari Aguirre 83, 48015 Bilbao, Vizcaya, Spain;Dpto. de Matemática Aplicada, Estadística e Investigación Operativa, Universidad del País Vasco, Leioa, Vizcaya, Spain;Dpto. de Matemática Aplicada, Estadística e Investigación Operativa, Universidad del País Vasco, Leioa, Vizcaya, Spain
Venue:
Computers and Operations Research
Year:
2009

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Abstract

We present an algorithmic approach for solving large-scale two-stage stochastic problems having mixed 0-1 first stage variables. The constraints in the first stage of the deterministic equivalent model have 0-1 variables and continuous variables, while the constraints in the second stage have only continuous. The approach uses the twin node family concept within the algorithmic framework, the so-called branch-and-fix coordination, in order to satisfy the nonanticipativity constraints. At the same time we consider a scenario cluster Benders decomposition scheme for solving large-scale LP submodels given at each TNF integer set. Some computational results are presented to demonstrate the efficiency of the proposed approach.