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A Hybrid Particle Swarm Optimization Algorithm for Solving Job Shop Scheduling Problems

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Theory, Methodology, Tools and Applications for Modeling and Simulation of Complex Systems (AsiaSim 2016, SCS AutumnSim 2016)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 644))

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Abstract

This paper proposes a new hybrid PSO optimization algorithm, which fuses GA and simulated annealing (SA) into the PSO algorithm. The crossover and mutation mechanism of GA algorithm make the new hybrid algorithm keep the diversity of population and retain the good factors in the population to jump out of local optimum. The sudden jump probability of SA also guarantees the diversity of the population, thus preventing local minimum of the hybrid PSO algorithm. This new hybrid algorithm is used to minimize the maximum completion time of the scheduling problems. The simulation results show that the performance of hybrid optimization algorithm outperforms another hybrid PSO algorithm. The hybrid PSO algorithm is not only in the structure of the algorithm, but also the search mechanism provides a powerful way to solve JSSP.

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Acknowledgements

The work was supported by the Aviation Science Fund of China No. 20141625003).

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Authors and Affiliations

  1. State CIMS Engineering Research Center at Tsinghua University, Beijing, 100084, China

    Qiaofeng Meng, Linxuan Zhang & Yushun Fan

Authors
  1. Qiaofeng Meng
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  2. Linxuan Zhang
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  3. Yushun Fan
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Corresponding author

Correspondence to Qiaofeng Meng .

Editor information

Editors and Affiliations

  1. Beihang University , Beijing, China

    Lin Zhang

  2. Beihang University , Beijing, China

    Xiao Song

  3. Beihang University , Beijing, China

    Yunjie Wu

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© 2016 Springer Science+Business Media Singapore

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Meng, Q., Zhang, L., Fan, Y. (2016). A Hybrid Particle Swarm Optimization Algorithm for Solving Job Shop Scheduling Problems. In: Zhang, L., Song, X., Wu, Y. (eds) Theory, Methodology, Tools and Applications for Modeling and Simulation of Complex Systems. AsiaSim SCS AutumnSim 2016 2016. Communications in Computer and Information Science, vol 644. Springer, Singapore. https://doi.org/10.1007/978-981-10-2666-9_8

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  • DOI: https://doi.org/10.1007/978-981-10-2666-9_8

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-2665-2

  • Online ISBN: 978-981-10-2666-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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