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Metaheuristics For The Mixed Shop Scheduling Problem

Author

Listed:
  • S. Q. LIU

    (Department of Industrial and Systems Engineering, National University of Singapore, 10 Kent Ridge Crescent, Singapore 119260, Singapore)

  • H. L. ONG

    (Department of Industrial and Systems Engineering, National University of Singapore, 10 Kent Ridge Crescent, Singapore 119260, Singapore)

Abstract

In this paper, three metaheuristics are proposed for solving a class of job shop, open shop, and mixed shop scheduling problems. We evaluate the performance of the proposed algorithms by means of a set of Lawrence's benchmark instances for the job shop problem, a set of randomly generated instances for the open shop problem, and a combined job shop and open shop test data for the mixed shop problem. The computational results show that the proposed algorithms perform extremely well on all these three types of shop scheduling problems. The results also reveal that the mixed shop problem is relatively easier to solve than the job shop problem due to the fact that the scheduling procedure becomes more flexible by the inclusion of more open shop jobs in the mixed shop.

Suggested Citation

  • S. Q. Liu & H. L. Ong, 2004. "Metaheuristics For The Mixed Shop Scheduling Problem," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 21(01), pages 97-115.
    • Handle: RePEc:wsi:apjorx:v:21:y:2004:i:01:n:s0217595904000072
    DOI: 10.1142/S0217595904000072
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    Citations

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    Cited by:

    1. Shi Qiang Liu & Erhan Kozan, 2011. "Scheduling Trains with Priorities: A No-Wait Blocking Parallel-Machine Job-Shop Scheduling Model," Transportation Science, INFORMS, vol. 45(2), pages 175-198, May.
    2. Xiang Chu & Qiu-Yan Zhong & Shahid G. Khokhar, 2015. "Triage Scheduling Optimization for Mass Casualty and Disaster Response," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 32(06), pages 1-20, December.

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