On efficient matheuristic algorithms for multi-period stochastic facility location-assignment problems
A. Unzueta Inchaurbe, L. F. Escudero Bueno, M. A. Garín Martín, C. Pizarro Romero
Discrete facility location-assignment decisions often have long lasting effects. Frequently, such decisions can be planned as a set of sequential actions to be implemented at different moments of a given time horizon. Usually, the computing time required for solving these type of problems is unaffordable by plain use of IP optimizers, so, decomposition and relaxation methodologies should be used. We present two matheuristic procedures to build bounds and feasible solutions by considering the solutions of relaxed problems. The first procedure is based on Scenario Cluster Lagrangean Decomposition for obtaining strong bounds of the solution value. The second procedure works with the relaxation of the integrality of subsets of variables for different levels of the problem. Additionally, and for both procedures, a lazy heuristic scheme, based on scenario clustering and on the solutions of the relaxed problems, is considered for obtaining a feasible solution of the full problem.
Palabras clave / Keywords: location-assignment, multi-period stochastic 0-1 optimization, scenario cluster Lagrangean problem, (dual) Lagrange multipliers updating, partial linear relaxation, lazy (primal) heuristic
Programado
Sesión M04 Optimización y Combinatoria
30 de mayo de 2018 15:30
Sala 5
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D. García Heredia, A. Alonso-Ayuso, E. Molina
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A. Alonso-Ayuso, L. Escudero, M. Guignard, A. Weintraub
I. Eguia Ribero, M. A. Garín Martín, A. Unzueta Inchaurbe
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