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A two-level Particle Swarm Optimisation algorithm on Job-Shop Scheduling Problems

Author

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  • Pisut Pongchairerks
  • Voratas Kachitvichyanukul

Abstract

The paper first presents an efficient PSO algorithm called GLN-PSOc. It is a variant of the standard PSO algorithm that requires a mapping procedure in order to solve a specific problem. Two mapping procedures are proposed in this paper for GLN-PSOc. The first mapping combined with GLN-PSOc is a heuristics for JSP and is called JSP-PSO. The second mapping combined with GLN-PSOc resulted in a parameter-tuning algorithm called PT-PSO. The combination of these two algorithms JSP-PSO and PT-PSO forms a two-level PSO. It is efficient and able to generate very good solutions on the benchmark instances.

Suggested Citation

  • Pisut Pongchairerks & Voratas Kachitvichyanukul, 2009. "A two-level Particle Swarm Optimisation algorithm on Job-Shop Scheduling Problems," International Journal of Operational Research, Inderscience Enterprises Ltd, vol. 4(4), pages 390-411.
    • Handle: RePEc:ids:ijores:v:4:y:2009:i:4:p:390-411
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    Cited by:

    1. Pisut Pongchairerks, 2019. "A Two-Level Metaheuristic Algorithm for the Job-Shop Scheduling Problem," Complexity, Hindawi, vol. 2019, pages 1-11, March.
    2. Wenkang Zhang & Yufan Zheng & Rafiq Ahmad, 2023. "The integrated process planning and scheduling of flexible job-shop-type remanufacturing systems using improved artificial bee colony algorithm," Journal of Intelligent Manufacturing, Springer, vol. 34(7), pages 2963-2988, October.

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