A genetic algorithm to solve the general multi-level lot-sizing problem with time-varying costs
Jonard, Nicolas; Dellaert, Nico; Jeunet, Jully (2000), A genetic algorithm to solve the general multi-level lot-sizing problem with time-varying costs, International Journal of Production Research, 38, 5, p. 241-257
TypeArticle accepté pour publication ou publié
Journal nameInternational Journal of Production Research
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Abstract (EN)We develop a genetic algorithm (GA) to solve the uncapacitated multilevel lotsizing problem in material requirements planning (MRP) systems. The major drawback of existing approaches is undoubtedly their inability to provide costefficient solutions in a reasonable computation time for realistic size problems involving general product structures. By contrast, the proposed GA can easily handle large product structures (more than 500 items) with numerous common parts, a problem type for which standard optimization software memory becomes rapidly insufficient. Based upon several hybrid operators and an original way to build up the initial population, the resultant GA provides in a moderate execution time high cost-effectiveness solutions compared with other techniques, in the extensive tests we performed.
Subjects / Keywordsgenetic algorithm
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