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Memetic algorithms for solving job-shop scheduling problems

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Abstract

The job-shop scheduling problem is well known for its complexity as an NP-hard problem. We have considered JSSPs with an objective of minimizing makespan while satisfying a number of hard constraints. In this paper, we developed a memetic algorithm (MA) for solving JSSPs. Three priority rules were designed, namely partial re-ordering, gap reduction and restricted swapping, and used as local search techniques in our MA. We have solved 40 benchmark problems and compared the results obtained with a number of established algorithms in the literature. The experimental results show that MA, as compared to GA, not only improves the quality of solutions but also reduces the overall computational time.

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Authors and Affiliations

  1. School of Information Technology and Electrical Engineering, University of New South Wales at the Australian Defence Force Academy, Nortchcott Drive, Canberra, ACT, 2600, Australia

    S. M. Kamrul Hasan, Ruhul Sarker, Daryl Essam & David Cornforth

Authors
  1. S. M. Kamrul Hasan
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  2. Ruhul Sarker
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  3. Daryl Essam
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  4. David Cornforth
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Correspondence to S. M. Kamrul Hasan.

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Hasan, S.M.K., Sarker, R., Essam, D. et al. Memetic algorithms for solving job-shop scheduling problems. Memetic Comp. 1, 69–83 (2009). https://doi.org/10.1007/s12293-008-0004-5

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  • DOI: https://doi.org/10.1007/s12293-008-0004-5

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