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Enhanced Hydrozoan Algorithm with Local Searches for Job-Shop Scheduling Problems

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Recent Advances in Information and Communication Technology 2021 (IC2IT 2021)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 251))

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Abstract

Job-Shop Scheduling Problem (JSSP) is one of the most difficult NP-Hard problems to solve. The goal of JSSP is to find a schedule of operations that minimizes the maximum completion time (or makespan) of n jobs with m machines. This work developed and evaluated an enhanced hydrozoan algorithm with local search strategies for efficiently solving JSSPs. The three incorporated local search strategies were one of the strengths of this algorithm, exploiting the local solution space thoroughly. Diverse exploration of global space was also enhanced by incorporation of a strong-parent crossover operator and three mutation operators. The evaluation was based on 18 widely used JSSP benchmark instances. The developed algorithm performed well, as intended; it provided the best solutions to all 18 instances that matched exactly with the best-known solutions reported in the literature. Our future work will be on attempting to apply the developed algorithm to flexible job shop problem, a more complex problem.

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Authors and Affiliations

  1. Computational Intelligence Laboratory, Faculty of Information Technology, King Mongkut’s Institute of Technology Ladkrabang, Bangkok, 10520, Thailand

    Daranat Tansui & Arit Thammano

Authors
  1. Daranat Tansui
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  2. Arit Thammano
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Corresponding author

Correspondence to Daranat Tansui .

Editor information

Editors and Affiliations

  1. Faculty of Information Technology and Digital Innovation, King Mongkut’s University of Technology North Bangkok, Bangkok, Thailand

    Phayung Meesad

  2. Faculty of Information Technology and Digital Innovation, King Mongkut's University of Technology North Bangkok, Bangkok, Thailand

    Dr. Sunantha Sodsee

  3. Faculty of IT and Digital Innovation, King Mongkut’s University of Technology North Bangkok, Bangkok, Thailand

    Watchareewan Jitsakul

  4. Faculty of Information Technology and Digital Innovation, King Mongkut’s University of Technology North Bangkok, Bangkok, Thailand

    Sakchai Tangwannawit

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Tansui, D., Thammano, A. (2021). Enhanced Hydrozoan Algorithm with Local Searches for Job-Shop Scheduling Problems. In: Meesad, P., Sodsee, D.S., Jitsakul, W., Tangwannawit, S. (eds) Recent Advances in Information and Communication Technology 2021. IC2IT 2021. Lecture Notes in Networks and Systems, vol 251. Springer, Cham. https://doi.org/10.1007/978-3-030-79757-7_24

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