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A Chaotic Differential Evolution Algorithm for Flexible Job Shop Scheduling

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Theory, Methodology, Tools and Applications for Modeling and Simulation of Complex Systems (AsiaSim 2016, SCS AutumnSim 2016)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 644))

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Abstract

To solve the flexible job shop scheduling problem (FJSP), a chaotic differential evolution algorithm (CDEA) is proposed with makespan minimization criterion. In the CDEA, logistic mapping is used to generate chaotic numbers for the initialization, because it is helpful to diversify the CDEA population and improve its performance in preventing premature convergence to local minima. A compositive operation-machine-based (COMB) encoding method is employed to reduce computational burden. Meanwhile, a self-adaptive double mutation scheme and an elitist strategy in the selection operator are introduced to balance the population diversity and the convergence rate. The performance of schedules is evaluated in terms of makespan and relative error. The results are compared with different well-known algorithm from open literatures. The results indicate that the proposed CDEA is effective in reducing makespan because the small value of relative error and the faster convergence rate are observed.

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Acknowledgements

This paper is partially supported by Aviation Foundation of China (2015ZG55018); Soft Science Research Project of Henan Province (132400410782); Key Science Research Project of Higher Education of Henan Province (15A630050); Technological Development Project of Zhengzhou City (20140583).

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Authors and Affiliations

  1. School of Mechatronics Engineering, Zhengzhou University of Aeronautics, Zhengzhou, China

    Haijun Zhang & Zhiqiang Jiang

  2. School of Management Engineering, Zhengzhou University of Aeronautics, Zhengzhou, China

    Qiong Yan & Guohui Zhang

Authors
  1. Haijun Zhang
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  2. Qiong Yan
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  3. Guohui Zhang
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  4. Zhiqiang Jiang
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Correspondence to Haijun Zhang .

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Editors and Affiliations

  1. Beihang University , Beijing, China

    Lin Zhang

  2. Beihang University , Beijing, China

    Xiao Song

  3. Beihang University , Beijing, China

    Yunjie Wu

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© 2016 Springer Science+Business Media Singapore

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Zhang, H., Yan, Q., Zhang, G., Jiang, Z. (2016). A Chaotic Differential Evolution Algorithm for Flexible Job Shop Scheduling. In: Zhang, L., Song, X., Wu, Y. (eds) Theory, Methodology, Tools and Applications for Modeling and Simulation of Complex Systems. AsiaSim SCS AutumnSim 2016 2016. Communications in Computer and Information Science, vol 644. Springer, Singapore. https://doi.org/10.1007/978-981-10-2666-9_9

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  • DOI: https://doi.org/10.1007/978-981-10-2666-9_9

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-2665-2

  • Online ISBN: 978-981-10-2666-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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