@ARTICLE{doi:10.1080/00207543.2011.588618,
  author = {Rabta, Boualem and Reiner, Gerald},
  title = {Batch sizes optimisation by means of queueing network decomposition
	and genetic algorithm},
  journal = {International Journal of Production Research},
  publisher = {Taylor \& Francis},
  year = {2012},
  volume = {50},
  pages = {2720-2731},
  number = {10},
  abstract = { 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. },
  doi = {10.1080/00207543.2011.588618},
  eprint = {http://www.tandfonline.com/doi/pdf/10.1080/00207543.2011.588618},
  gsid = {16200156439986147595},
  url = {http://www.tandfonline.com/doi/abs/10.1080/00207543.2011.588618}
}