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Genetic algorithms for a supply management problem: MIP-recombination vs greedy decoder

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  • Borisovsky, P.
  • Dolgui, A.
  • Eremeev, A.

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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  • Borisovsky, P. & Dolgui, A. & Eremeev, A., 2009. "Genetic algorithms for a supply management problem: MIP-recombination vs greedy decoder," European Journal of Operational Research, Elsevier, vol. 195(3), pages 770-779, June.
    • Handle: RePEc:eee:ejores:v:195:y:2009:i:3:p:770-779
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