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Link to original content: https://doi.org/10.1007/978-3-540-28633-2_40
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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

  1. Jain, A.S., Meeran, S.: A state-of-the-art review of job-shop scheduling techniques. Department of Applied Physics, Electronic and Mechanical Engineering, University of Dundee, Dundee, Scotland, UK

    Google Scholar 

  2. Jacek, B., Wolfgang, D., Erwin, P.: The job shop scheduling problem: conventional and new solution techniques. European journal of operational research 93, 1–33 (1996)

    Article  MATH  Google Scholar 

  3. Cheng, R., Gen, M., Tsujimura, Y.: A Tutorial Survey of Job-Shop Scheduling Problems using Genetic Algorithms-I. Representation, Computers & Industrial Engineering 30(4), 983–997 (1996)

    Article  Google Scholar 

  4. Yamada, T., Nakano, R.: Job-shop Scheduling. In: Genetic Algorithm in Engineering Systems. IEE control engineering series, vol. 55 (1997)

    Google Scholar 

  5. Liang, Y.C., Ge, H.W., Zhou, C.G., Lee, H.P., Lin, W.Z., Lim, S.P., Lee, K.H.: Solving traveling salesman problems by genetic algorithms. Progress in Natural Science 13(2), 1–7 (2003)

    MathSciNet  Google Scholar 

  6. Fisher, H., Thompson, L.: Probabilistic learning combination of local job-shop scheduling rules. In: Industrial Scheduling, Prentice Hall, Englewood Cliffs (1963)

    Google Scholar 

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Author information

Authors and Affiliations

  1. College of Computer Science and Technology, Jilin University, Key Laboratory of Symbol Computation and Knowledge Engineering of the Ministry of Education, Changchun, 130012, China

    Chunguo Wu, Yanchun Liang & Chunguang Zhou

  2. Institute of High Performance Computing, Singapore, 117528, Singapore

    Wei Xiang, Yanchun Liang & Heow Pueh Lee

Authors
  1. Chunguo Wu
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  2. Wei Xiang
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  3. Yanchun Liang
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  4. Heow Pueh Lee
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  5. Chunguang Zhou
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Editor information

Editors and Affiliations

  1. Faculty of Engineering and Information Technology, Centre for Quantum Computation and Intelligent Systems, and Australian ACS National Committee for Artificial Intelligence, University of Technology, Sydney, Australia

    Chengqi Zhang

  2. Department of Computer Science, Auckland University of Technology, 1020, Auckland, New Zealand

    Hans W. Guesgen

  3. Artificial Intelligence Technology Centre, Auckland University of Technology, Auckland, New Zealand

    Wai-Kiang Yeap

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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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