Abstract
This article models a multi-vehicle material handling system as a closed-loop queueing network with finite buffers and general service times, where the vehicles represent the jobs in the network. This type of network differs from other queueing systems, because the vehicles’ residence times on track segments (servers) depend on the number of jobs (vehicles) in circulation. A new iterative approximation algorithm is presented that estimates throughput capacity and decomposes the network consisting of S servers into S separate G/G/1 systems. Each subsystem is analyzed separately to estimate the work-in-process via a population constraint to ensure that the summation of the average buffer sizes across all servers equals the total number of vehicles. Numerical results show that the methodology proposed is accurate in a wide range of operating scenarios.
Acknowledgements
The author is grateful to the three anonymous reviewers and to Spyros Reveliotis, the Associate Editor, for suggestions that improved the content and structure of the article.