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A Differential Evolution Approach for NTJ-NFSSP with SDSTs and RDs

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Intelligent Computing Theories and Applications (ICIC 2012)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7390))

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Abstract

In this paper, an efficient differential evolution approach, namely DE_NTJ, is presented to minimize the number of tardy jobs (NTJ) for the no-wait flow-shop scheduling problem (NFSSP) with sequence-dependent setup times (SDSTs) and release dates (RDs), which is a complex problem and can be abbreviated as NTJ-NFSSP with SDSTs and RDs. To balance the exploration and exploitation abilities of our DE_NTJ, DE-based global search is utilized to obtain the promising regions or solutions over the solution space, and a local search based on the interchange-based neighborhood and problem’s properties is developed to exploit the neighborhoods from these regions. Simulation results based on a set of random instances show the superiority of DE_NTJ in terms of searching quality, efficiency, and robustness.

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Author information

Authors and Affiliations

  1. Department of Automation, Kunming University of Science and Technology, Kunming, 650500, China

    Rong Hu, Xianghu Meng, Bin Qian & Kun Li

Authors
  1. Rong Hu
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  2. Xianghu Meng
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  3. Bin Qian
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  4. Kun Li
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Editor information

Editors and Affiliations

  1. School of Electronics and Information Engineering, Machine Learning and Systems Biology Laboratory, Tongji University, 4800 Caoan Road, 201804, Shanghai, China

    De-Shuang Huang

  2. Faculty of Computer and Information Sciences, Hosei University, 3-7-2, Kajino-Cho, Koganei-Shi, Japan

    Jianhua Ma

  3. School of Electrical Engineering, University of Ulsan, #7-413, San 29, Muger Dong, 680-749, Ulsan, South Korea

    Kang-Hyun Jo

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

    M. Michael Gromiha

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© 2012 Springer-Verlag Berlin Heidelberg

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Hu, R., Meng, X., Qian, B., Li, K. (2012). A Differential Evolution Approach for NTJ-NFSSP with SDSTs and RDs. In: Huang, DS., Ma, J., Jo, KH., Gromiha, M.M. (eds) Intelligent Computing Theories and Applications. ICIC 2012. Lecture Notes in Computer Science(), vol 7390. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31576-3_38

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  • DOI: https://doi.org/10.1007/978-3-642-31576-3_38

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-31575-6

  • Online ISBN: 978-3-642-31576-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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