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Controlling Search Using an S Decreasing Constriction Factor for Solving Multi-mode Scheduling Problems

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Recent Trends in Applied Artificial Intelligence (IEA/AIE 2013)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7906))

Abstract

The multi-mode resource-constrained project scheduling problem (MRCPSP) is an important issue for industry, and has been confirmed to be an NP-hard problem. The particle swarm optimization meta-heuristic is an effective and promising method and well applied to solve a variety of NP application problems. MRCPSP involves two sub-problems: the activity mode selection and the activity order sub-problems. Therefore, a discrete version PSO and constriction version PSO were applied for solving these two sub-problems respectively. Discrete PSO is utilized for determining the activity operation mode, the constriction PSO is applied for deciding the activity order. To enhance the exploration and exploitation search so as to improve search efficiency, an S decreasing constriction factor adjustment mechanism was proposed. To verify the performance of proposed scheme, instances of MRCPSP in PSPLIB were tested and comparisons with other state-of-art algorithms were also conducted. The experimental results reveal that the proposed S decreasing constriction factor adjustment scheme is efficient for solving MRCPSP type scheduling problems.

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Author information

Authors and Affiliations

  1. Computer Science and Information Engineering, National Chin-Yi University of Technology, Taichung, 411, Taiwan, R.O.C

    Reuy-Maw Chen & Chuin-Mu Wang

Authors
  1. Reuy-Maw Chen
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  2. Chuin-Mu Wang
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Editor information

Editors and Affiliations

  1. Department of Computer Science, Texas State University, 78666, San Marcos, TX, USA

    Moonis Ali

  2. Agent Systems Research Group, Department of Computer Science, Faculty of Sciences, VU University Amsterdam, De Boelelaan 1081, 1081, Amsterdam, HV, The Netherlands

    Tibor Bosse

  3. Interactive Intelligence Group, Department of Intelligent Systems, Faculty of Electrical Engineering, Mathematics and Computer Science, Delft University of Technology, Mekelweg 4, 2628 CD, Delft, The Netherlands

    Koen V. Hindriks  & Catholijn M. Jonker  & 

  4. Computational Intelligence Group, Department of Computer Science, Faculty of Sciences, VU University Amsterdam, De Boelelaan 1081, 1081 HV, Amsterdam, The Netherlands

    Mark Hoogendoorn

  5. Agent Systems Research Group, Department of Computer Science, Faculty of Sciences, VU University Amsterdam, De Boelelaan 1081, 1081 HV, Amsterdam, The Netherlands

    Jan Treur

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© 2013 Springer-Verlag Berlin Heidelberg

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Chen, RM., Wang, CM. (2013). Controlling Search Using an S Decreasing Constriction Factor for Solving Multi-mode Scheduling Problems . In: Ali, M., Bosse, T., Hindriks, K.V., Hoogendoorn, M., Jonker, C.M., Treur, J. (eds) Recent Trends in Applied Artificial Intelligence. IEA/AIE 2013. Lecture Notes in Computer Science(), vol 7906. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38577-3_56

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  • DOI: https://doi.org/10.1007/978-3-642-38577-3_56

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-38576-6

  • Online ISBN: 978-3-642-38577-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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