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2015 | OriginalPaper | Chapter

Job Shop Scheduling with Alternative Machines Using a Genetic Algorithm Incorporating Heuristic Rules -Effectiveness of Due-Date Related Information-

Authors : Parinya Kaweegitbundit, Toru Eguchi

Published in: Advances in Production Management Systems: Innovative Production Management Towards Sustainable Growth

Publisher: Springer International Publishing

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Abstract

This paper deals with an efficient scheduling method for job shop scheduling with alternative machines with the objective to minimize mean tardiness. The method uses a genetic algorithm incorporating heuristic rules for job sequencing and machine selection. Effective heuristic rules for this method have been proposed so far. However due-date related information has not been included in the heuristic rule for machine selection even though the objective is to minimize mean tardiness. This paper examines the effectiveness of due-date related information for machine selection in this method through numerical experiments.

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Kaweegitbundit, P., Eguchi, T.: Job shop scheduling with alternative machines using genetic algorithm incorporating heuristic rules. In: Mechanical Engineering Congress, 2014 Japan[MECJ-14], No. 14-1, S1420140. The Japan Society of Mechanical Engineers, Tokyo (2014)
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Eguchi, T., Kaweegitbundit, P., Hoshino, N., Daido, T., Murayama, T.: Job shop scheduling with alternative machines–experimental evaluation of the scheduling method using a genetic algorithm incorporating heuristic rules–. In: Manufacturing Systems Division Conference 2015, No. 15-8, pp. 95–96. The Japan Society of Mechanical Engineers, Tokyo (2015)
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Metadata
Title
Job Shop Scheduling with Alternative Machines Using a Genetic Algorithm Incorporating Heuristic Rules -Effectiveness of Due-Date Related Information-
Authors
Parinya Kaweegitbundit
Toru Eguchi
Copyright Year
2015
Book
Advances in Production Management Systems: Innovative Production Management Towards Sustainable Growth

Print ISBN: 978-3-319-22755-9

Electronic ISBN: 978-3-319-22756-6

Copyright Year: 2015

DOI
https://doi.org/10.1007/978-3-319-22756-6_54

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