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

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3 Author(s)
Chan, F.T.S. ; Dept. of Ind. & Manuf. Syst. Eng., Hong Kong Univ., China ; Wong, T.C. ; Chan, P.L.Y.

A novel approach to solve equal size lot streaming (ESLS) in job-shop scheduling problem (JSP) using genetic algorithms (GA) is proposed. LS refer 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 GA. 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.

Published in:

Intelligent Control, 2004. Proceedings of the 2004 IEEE International Symposium on

Date of Conference:

2-4 Sept. 2004