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An Improved Discrete Artificial Bee Colony Algorithm for Hybrid Flow Shop Problems

  • Conference paper
Intelligent Computing for Sustainable Energy and Environment (ICSEE 2012)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 355))

Abstract

Being a typical NP-hard combinatorial optimization problem, the hybrid flow shop (HFS) problem widely exists in manufacturing systems. In this paper, we firstly establish the model of the HFS problem by employing the vector representation. Then an improved discrete artificial bee colony (IDABC) algorithm is proposed for this problem to minimize the makespan. In the IDABC algorithm, a novel differential evolution and a modified variable neighborhood search are studied to generating new solutions for the employed and onlooker bees. The destruction and construction procedures are utilized to obtain solutions for the scout bees. The simulation results clearly imply that the proposed IDABC algorithm is highly effective and efficient as compared to six state-of-the-art algorithms on the same benchmark instances.

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Author information

Authors and Affiliations

  1. Key Laboratory of Advanced Control and Optimization for Chemical Process, Ministry of Education, East China University of Science and Technology, Shanghai, 200237, China

    Zhe Cui & Xingsheng Gu

Authors
  1. Zhe Cui
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  2. Xingsheng Gu
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Editor information

Editors and Affiliations

  1. School of Electronics, Electrical Engineering and Computer Science, Queen’s University Belfast, Ashby Building, Stranmillis Road, BT9 5AH, Belfast, UK

    Kang Li

  2. Department of Automation, Shanghai Jiao Tong University, 800 Dongchuan Road, 200240, Shanghai, China

    Shaoyuan Li  & Dewei Li  & 

  3. School of Mechatronics Engineering and Automation, Shanghai University, 149 Yanchang Road, 200072, Shanghai, China

    Qun Niu

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Cui, Z., Gu, X. (2013). An Improved Discrete Artificial Bee Colony Algorithm for Hybrid Flow Shop Problems. In: Li, K., Li, S., Li, D., Niu, Q. (eds) Intelligent Computing for Sustainable Energy and Environment. ICSEE 2012. Communications in Computer and Information Science, vol 355. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37105-9_33

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  • DOI: https://doi.org/10.1007/978-3-642-37105-9_33

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-37104-2

  • Online ISBN: 978-3-642-37105-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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