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Batch Sizes Optimization by means of Queueing Network Decomposition and Genetic Algorithm
Résumé Batch sizes have a considerable impact on the performance of a manufacturing process. Determining optimal values for batch sizes helps to reduce inventories/costs and lead times. The deterministic nature of the available batch size optimisation models reduces the practical value of the obtained solutions. Other models focus only on critical parts of the system (e.g., the bottleneck). In this paper, we present an approach that overcomes important limitations of such simplified solutions. We describe a combination of queueing network analysis and a genetic algorithm that allows us to take into account the real characteristics of the system when benefiting from an efficient optimisation mechanism. We are able to demonstrate that the application of our approach on a real-sized problem with 49 products allows us to obtain a solution (values for batch sizes) with less than 4% relative deviation of the cycle time from the exact minimal value.
   
Mots-clés batch sizing, decomposition, genetic algorithms, manufacturing systems, optimisation, queueing networks
   
Citation Rabta, B., & Reiner, G. (2012). Batch Sizes Optimization by means of Queueing Network Decomposition and Genetic Algorithm. International Journal of Production Research, 50(10), 2720-2731.
   
Type Article de périodique (Anglais)
Date de publication 17-8-2012
Nom du périodique International Journal of Production Research
Volume 50
Numéro 10
Pages 2720-2731
URL http://dx.doi.org/10.1080/00207543.2011.588618