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Improved Particle Swarm Optimization for RCP Scheduling Problem

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The Sixth International Symposium on Neural Networks (ISNN 2009)

Part of the book series: Advances in Intelligent and Soft Computing ((AINSC,volume 56))

Abstract

In this paper, an improved particle swarm optimization (IPSO) algorithm is presented to solve RCP Scheduling Problem. Firstly, a mapping is created between the feasible schedule and the position of the particle, then the IPSO begin to search the global best and the local best until the stop criteria is satisfied. A case study is presented and a comparison is made between IPSO and some traditional heuristic methods. Results show that the IPSO algorithm is more satisfying than those of the heuristic methods in terms of feasibility and efficiency.

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Author information

Authors and Affiliations

  1. School of Business and Management, North China Electric Power University, Beijing, 102206, China

    Qiang Wang & Jianxun Qi

Authors
  1. Qiang Wang
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  2. Jianxun Qi
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Editor information

Editors and Affiliations

  1. Department of Control Science and Engineering, Huazhong University of Science and Technology, No. 1037, Luoyu Road, 430074, Wuhan, Hubei, China

    Hongwei Wang , Yi Shen  & Zhigang Zeng ,  & 

  2. Texas A&M University at Qatar, PO Box 23874, Doha, Qatar,  

    Tingwen Huang

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Wang, Q., Qi, J. (2009). Improved Particle Swarm Optimization for RCP Scheduling Problem. In: Wang, H., Shen, Y., Huang, T., Zeng, Z. (eds) The Sixth International Symposium on Neural Networks (ISNN 2009). Advances in Intelligent and Soft Computing, vol 56. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01216-7_6

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  • DOI: https://doi.org/10.1007/978-3-642-01216-7_6

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-01215-0

  • Online ISBN: 978-3-642-01216-7

  • eBook Packages: EngineeringEngineering (R0)

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