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Hybrid genetic algorithm for bi-objective flow shop scheduling problems with re-entrant jobs

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2 Author(s)
Lee, C.K.M. ; Sch. of Mech. & Aerosp. Eng., Nanyang Technol. Univ., Singapore, Singapore ; Danping Lin

This paper presents a simulated genetic algorithm model of scheduling the flow shop problems with re-entrant jobs. The objectives of this research are to minimize the weighted tardiness and makespan. The proposed model considers that the jobs with non-identical due dates are processed on the machines with the same order. Furthermore, the re-entrant jobs are stochastic as only some jobs are required to reenter to the flow shop. The tardiness weight is adjusted once the jobs re-enter the shop. The performance of the proposed GA model is verified by a number of numerical experiments where the data come from the case company. The results show the proposed method has a higher order satisfaction rate than the industrial practices.

Published in:

Industrial Engineering and Engineering Management (IEEM), 2010 IEEE International Conference on

Date of Conference:

7-10 Dec. 2010