Equal size lot streaming to job-shop scheduling problem using genetic algorithms

Tools

Chan, F. T. S. and Wong, T. C. and Chan, L. Y.; (2004) Equal size lot streaming to job-shop scheduling problem using genetic algorithms. In: Proceedings of the 2004 IEEE International Symposium on Intelligent Control, 2004. IEEE, New York, pp. 472-476. ISBN 0780386353 (https://doi.org/10.1109/ISIC.2004.1387729)

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Abstract

A novel approach to solve Equal Size Lot Streaming (ESLS) in Job-shop Scheduling Problem (JSP) using Genetic Algorithms (GAs) is proposed. LS refers to a situation that a lot can be split into a number of smaller lots (or sub-lots) so that successive operation can be overlapped. By adopting the proposed approach, the sub-lot number for different lots and the processing sequence of all sub-lots can be determined simultaneously using GAs. Applying Just-In-Time (JIT) policy, the results show that the solution can minimize both the overall penalty cost and total setup time with the development of multi-objective function. In this connection, decision makers can then assign various weightings so as to enhance the reliability of the final solution.

ORCID iDs

Chan, F. T. S., Wong, T. C. ORCID logoORCID: https://orcid.org/0000-0001-8942-1984 and Chan, L. Y.;
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