Please use this identifier to cite or link to this item: https://doi.org/10.1080/00207540701644219
Title: Performance of an ant colony optimisation algorithm in dynamic job shop scheduling problems
Authors: Zhou, R. 
Nee, A.Y.C. 
Lee, H.P. 
Keywords: Ant colony optimisation
Dispatching rules
Dynamic job shop scheduling
Issue Date: Jan-2009
Citation: Zhou, R., Nee, A.Y.C., Lee, H.P. (2009-01). Performance of an ant colony optimisation algorithm in dynamic job shop scheduling problems. International Journal of Production Research 47 (11) : 2903-2920. ScholarBank@NUS Repository. https://doi.org/10.1080/00207540701644219
Abstract: The goal of the current study is to identify appropriate application domains of Ant Colony Optimisation (ACO) in the area of dynamic job shop scheduling problem. The algorithm is tested in a shop floor scenario with three levels of machine utilisations, three different processing time distributions, and three different performance measures for intermediate scheduling problems. The steady-state performances of ACO in terms of mean flow time, mean tardiness, total throughput on different experimental environments are compared with those from dispatching rules including first-in-first-out, shortest processing time, and minimum slack time. Two series of experiments are carried out to identify the best ACO strategy and the best performing dispatching rule. Those two approaches are thereafter compared with different variations of processing times. The experimental results show that ACO outperforms other approaches when the machine utilisation or the variation of processing times is not high.
Source Title: International Journal of Production Research
URI: http://scholarbank.nus.edu.sg/handle/10635/61077
ISSN: 00207543
DOI: 10.1080/00207540701644219
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