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

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

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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.