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Flexible Job Shop Scheduling Using a Multiobjective Memetic Algorithm

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Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence (ICIC 2011)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6839))

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Abstract

This paper addresses the flexible job shop scheduling problem with minimization of the makespan, maximum machine workload, and total machine workload as the objectives. A multiobjective memetic algorithm is proposed. It belongs to the integrated approach, which deals with the routing and sequencing sub-problems together. Dominance-based and aggregation-based fitness assignment methods are used in the parts of genetic algorithm and local search, respectively. The local search procedure follows the framework of variable neighborhood descent algorithm. The proposed algorithm is compared with three benchmark algorithms using fifteen classic problem instances. Its performance is better in terms of the number and quality of the obtained solutions.

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Author information

Authors and Affiliations

  1. Department of Computer Science and Information Engineering, National Taiwan Normal University, Taiwan, R.O.C.

    Tsung-Che Chiang & Hsiao-Jou Lin

Authors
  1. Tsung-Che Chiang
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  2. Hsiao-Jou Lin
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Editor information

Editors and Affiliations

  1. School of Electronics and Information Engineering, Tongji University, 4800 Caoan Road, 201804, Shanghai, China

    De-Shuang Huang

  2. School of Computer and Communication Engineering, Zhengzhou University of Light Industry, No. 5, Dongfeng Road, Jinshui District, 450002, Zhengzhou, Henan, China

    Yong Gan

  3. Indian Institute of Technology Kanpur, 208016, Kanpur, India

    Phalguni Gupta

  4. Department of Biotechnology, Indian Institute of Technology Madras, 600 036, Chennai, Tamilnadu, India

    M. Michael Gromiha

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© 2012 Springer-Verlag Berlin Heidelberg

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Chiang, TC., Lin, HJ. (2012). Flexible Job Shop Scheduling Using a Multiobjective Memetic Algorithm. In: Huang, DS., Gan, Y., Gupta, P., Gromiha, M.M. (eds) Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence. ICIC 2011. Lecture Notes in Computer Science(), vol 6839. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25944-9_7

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  • DOI: https://doi.org/10.1007/978-3-642-25944-9_7

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-25943-2

  • Online ISBN: 978-3-642-25944-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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