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Solving hybrid flow shop scheduling problems using bat algorithm

Author

Listed:
  • M.K. Marichelvam
  • T. Prabaharan
  • Xin-She Yang
  • M. Geetha

Abstract

This paper investigates the multistage hybrid flow shop (HFS) scheduling problems using the new bat algorithm. A HFS is the generalisation of flowshop with multiple machines. HFS is one of the important scheduling problems that represent many industries like iron and steel, chemical, textile and ceramic industries. The HFS scheduling problems have been proved to be NP-hard. A recently developed bat meta-heuristic algorithm is proposed to solve the HFS problems. The proposed algorithm is validated with a well-chosen set of benchmark problems in the literature. Computational results indicate that the proposed bat algorithm is more efficient than the genetic algorithm and particle swarm optimisation.

Suggested Citation

  • M.K. Marichelvam & T. Prabaharan & Xin-She Yang & M. Geetha, 2013. "Solving hybrid flow shop scheduling problems using bat algorithm," International Journal of Logistics Economics and Globalisation, Inderscience Enterprises Ltd, vol. 5(1), pages 15-29.
    • Handle: RePEc:ids:injleg:v:5:y:2013:i:1:p:15-29
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    Citations

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    Cited by:

    1. Alfaro-Fernández, Pedro & Ruiz, Rubén & Pagnozzi, Federico & Stützle, Thomas, 2020. "Automatic Algorithm Design for Hybrid Flowshop Scheduling Problems," European Journal of Operational Research, Elsevier, vol. 282(3), pages 835-845.
    2. Mohamadreza Dabiri & Mehdi Yazdani & Bahman Naderi & Hassan Haleh, 2022. "Modeling and solution methods for hybrid flow shop scheduling problem with job rejection," Operational Research, Springer, vol. 22(3), pages 2721-2765, July.
    3. Pei, Jun & Liu, Xinbao & Fan, Wenjuan & Pardalos, Panos M. & Lu, Shaojun, 2019. "A hybrid BA-VNS algorithm for coordinated serial-batching scheduling with deteriorating jobs, financial budget, and resource constraint in multiple manufacturers," Omega, Elsevier, vol. 82(C), pages 55-69.

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