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

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 up...

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Bibliographic Details
Published in:European journal of operational research 2009-06, Vol.195 (3), p.770-779
Main Authors: Borisovsky, P., Dolgui, A., Eremeev, A.
Format: Article
Language:English
Subjects:
Comparative analysis
Genetic algorithms
Genetic algorithms Integer programming Recombination operators Supply chain management
Integer programming
Recombination operators
Studies
Supply chain management
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Summary: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.
ISSN:0377-2217
1872-6860
DOI:10.1016/j.ejor.2007.06.060