Please use this identifier to cite or link to this item: https://doi.org/10.1023/A:1024653810491
Title: A modified genetic algorithm for distributed scheduling problems
Authors: Jia, H.Z. 
Nee, A.Y.C. 
Fuh, J.Y.H. 
Zhang, Y.F. 
Keywords: Distributed production
Distributed scheduling
Genetic algorithms
Issue Date: Jun-2003
Source: Jia, H.Z., Nee, A.Y.C., Fuh, J.Y.H., Zhang, Y.F. (2003-06). A modified genetic algorithm for distributed scheduling problems. Journal of Intelligent Manufacturing 14 (3-4) : 351-362. ScholarBank@NUS Repository. https://doi.org/10.1023/A:1024653810491
Abstract: Genetic algorithms (GAs) have been widely applied to the scheduling and sequencing problems due to its applicability to different domains and the capability in obtaining near-optimal results. Many investigated GAs are mainly concentrated on the traditional single factory or single job-shop scheduling problems. However, with the increasing popularity of distributed, or globalized production, the previously used GAs are required to be further explored in order to deal with the newly emerged distributed scheduling problems. In this paper, a modified GA is presented, which is capable of solving traditional scheduling problems as well as distributed scheduling problems. Various scheduling objectives can be achieved including minimizing makespan, cost and weighted multiple criteria. The proposed algorithm has been evaluated with satisfactory results through several classical scheduling benchmarks. Furthermore, the capability of the modified GA was also tested for handling the distributed scheduling problems.
Source Title: Journal of Intelligent Manufacturing
URI: http://scholarbank.nus.edu.sg/handle/10635/54423
ISSN: 09565515
DOI: 10.1023/A:1024653810491
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