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Genetic Algorithms for a Supply Management Problem : MIP-Recombination vs Greedy Decoder

P. Borisovsky Alexandre Dolgui 1 A. Eremeev 
1 Laboratoire en Sciences et Technologies de l'Information
MSGI-ENSMSE - Département Méthodes Scientifiques pour la Gestion Industrielle
Abstract : Two variants of genetic algorithm (GA) for solving the Supply Management Problem with Lower-Bounded Demands (SMPLD) are proposed and experimentally tested. The SMPLD problem consists in planning the shipments from a set of suppliers to a set of customers minimizing the total cost, given lower and upper bounds on shipment sizes, lower-bounded consumption and linear costs for opened deliveries. The first variant of GA uses the standard binary representation of solutions and a new recombination operator based on the mixed integer programming (MIP) techniques. The second GA is based on the permutation representation and a greedy decoder. Our experiments indicate that the GA with MIP-recombination compares favorably to the other GA and to the MIP-solver CPLEX 9.0 in terms of cost of obtained solutions. The GA based on greedy decoder is shown to be the most robust in finding feasible solutions.
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Submitted on : Monday, May 25, 2009 - 5:45:57 PM
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P. Borisovsky, Alexandre Dolgui, A. Eremeev. Genetic Algorithms for a Supply Management Problem : MIP-Recombination vs Greedy Decoder. European Journal of Operational Research, Elsevier, 2009, 195 (3), pp.770-779. ⟨10.1016/j.ejor.2007.06.060⟩. ⟨hal-00387691⟩



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