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A Modified Integer-Coding Genetic Algorithm for Job Shop Scheduling Problem

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PRICAI 2004: Trends in Artificial Intelligence (PRICAI 2004)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3157))

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Abstract

An operation template is proposed in this paper for describing the mapping between operations and a subset of natural numbers. With such operation template, a job shop scheduling problem (JSSP) can be transformed into a traveling salesman problem (TSP), hence the integer-coding genetic algorithm for TSP can be easily applied and modified. A decoding strategy, called virtual job shop, is proposed to evaluate the fitness of the individual in GA population. The integration of the operation template and virtual job shop makes the existing integer-coding GA possible for solving an extension of a classical job shop scheduling problem.

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References

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© 2004 Springer-Verlag Berlin Heidelberg

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Wu, C., Xiang, W., Liang, Y., Lee, H.P., Zhou, C. (2004). A Modified Integer-Coding Genetic Algorithm for Job Shop Scheduling Problem. In: Zhang, C., W. Guesgen, H., Yeap, WK. (eds) PRICAI 2004: Trends in Artificial Intelligence. PRICAI 2004. Lecture Notes in Computer Science(), vol 3157. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-28633-2_40

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  • DOI: https://doi.org/10.1007/978-3-540-28633-2_40

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-22817-2

  • Online ISBN: 978-3-540-28633-2

  • eBook Packages: Springer Book Archive

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