Design of a genetic algorithm for bi-objective flow shop scheduling problems with re-entrant jobs

Lee, Carman K.M., Lin, Danping, Ho, William and Wu, Zhang (2011). Design of a genetic algorithm for bi-objective flow shop scheduling problems with re-entrant jobs. International Journal of Advanced Manufacturing Technology, 56 (9-12), pp. 1105-1113.

Abstract

This paper presents a simulated genetic algorithm (GA) model of scheduling the flow shop problem with re-entrant jobs. The objective of this research is to minimize the weighted tardiness and makespan. The proposed model considers that the jobs with non-identical due dates are processed on the machines in 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 reenter to 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 current industrial practices.

Publication DOI: https://doi.org/10.1007/s00170-011-3251-4
Divisions: Aston Business School > Operations & Information Management
Aston Business School
Additional Information: © Springer-Verlag London Limited 2011. The final publication is available at Springer via http://dx.doi.org/10.1007/s00170-011-3251-4
Uncontrolled Keywords: bi-objective,flow shop,genetic algorithm,re-entrant ,Industrial and Manufacturing Engineering,Control and Systems Engineering,Computer Science Applications,Software,Mechanical Engineering
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Related URLs: http://www.scop ... tnerID=8YFLogxK (Scopus URL)
http://link.spr ... 0170-011-3251-4 (Publisher URL)
Published Date: 2011-10-01
Authors: Lee, Carman K.M.
Lin, Danping
Ho, William
Wu, Zhang

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