@article{becker2005optimisation,
	abstract = {In this article we use the Ant Colony Optimisation (AGO) algorithm in order to find optimal Kanban allocations in Kanban systems represented by Stochastic Petri Net (SPN) models. Like other optimisation algorithms inspired by nature, such as Simulated Annealing/Genetic Algorithms, the AGO algorithm contains a large number of adjustable parameters. Thus we study the influence of the parameters on performance of AGO on the Kanban allocation problem, and identify the most important parameters.},
	title = {Optimisation of buffer size in manufacturing systems using ant algorithms},
	author = {Becker, Matthias and Szczerbicka, Helena},
	year = {2005},
	papertype = {fullpaper}
}