Genetic Algorithms with Simulation for a Job Shop Scheduling Problem with Crane Conveyance

Abstract : In this paper, a genetic algorithm (GA) and GA with diversification generator (DG) for solving scheduling problems with crane conveyance are proposed. It becomes very difficult to obtain an optimum or near optimum schedule under consideration of restrictions to avoid crane interference in addition to many restrictions on operation of each machine. GA-based algorithms are applied to obtain high quality crane assignment which successfully leads to few working hour delays caused by crane interference. Effectiveness of this algorithm is confirmed by numerical experiments.
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Communication dans un congrès
Hermann Lödding; Ralph Riedel; Klaus-Dieter Thoben; Gregor von Cieminski; Dimitris Kiritsis. IFIP International Conference on Advances in Production Management Systems (APMS), Sep 2017, Hamburg, Germany. Springer International Publishing, IFIP Advances in Information and Communication Technology, AICT-513 (Part I), pp.483-491, 2017, Advances in Production Management Systems. The Path to Intelligent, Collaborative and Sustainable Manufacturing 〈10.1007/978-3-319-66923-6_57〉
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Soumis le : lundi 18 décembre 2017 - 10:38:40
Dernière modification le : lundi 18 décembre 2017 - 11:02:24

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Takashi Tanizaki, Hideaki Katagiri. Genetic Algorithms with Simulation for a Job Shop Scheduling Problem with Crane Conveyance. Hermann Lödding; Ralph Riedel; Klaus-Dieter Thoben; Gregor von Cieminski; Dimitris Kiritsis. IFIP International Conference on Advances in Production Management Systems (APMS), Sep 2017, Hamburg, Germany. Springer International Publishing, IFIP Advances in Information and Communication Technology, AICT-513 (Part I), pp.483-491, 2017, Advances in Production Management Systems. The Path to Intelligent, Collaborative and Sustainable Manufacturing 〈10.1007/978-3-319-66923-6_57〉. 〈hal-01666172〉

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