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The just-in-time job-shop scheduling problem with distinct due-dates for operations

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Abstract

In the just-in-time job-shop scheduling (JIT–JSS) problem every operation has a distinct due-date, and earliness and tardiness penalties. Any deviation from the due-date incurs penalties. The objective of JIT–JSS is to obtain a schedule, i.e., the completion time for performing the operations, with the smallest total (weighted) earliness and tardiness penalties. This paper presents a matheuristic algorithm for the JIT–JSS problem, which operates by decomposing the problem into smaller sub-problems, optimizing the sub-problems and delivering the optimal schedule for the problem. By solving a set of 72 benchmark instances ranging from 10 to 20 jobs and 20 to 200 operations we show that the proposed algorithm outperforms the state-of-the-art methods and the solver CPLEX, and obtains new best solutions for nearly 56% of the instances, including for 79% of the large instances with 20 jobs.

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Acknowledgements

We thank the guest editors and the anonymous referees for their valuable and constructive comments on the earlier version of the paper. Mohammad Mahdi Ahmadian is the recipient of the UTS International Research Scholarship (IRS) and UTS Faculty of Science Scholarship. Amir Salehipour is the recipient of an Australian Research Council Discovery Early Career Researcher Award (Project Number DE170100234) funded by the Australian Government.

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  1. School of Mathematical and Physical Sciences, University of Technology Sydney, Sydney, Australia

    Mohammad Mahdi Ahmadian & Amir Salehipour

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  1. Mohammad Mahdi Ahmadian
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Correspondence to Amir Salehipour.

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Ahmadian, M.M., Salehipour, A. The just-in-time job-shop scheduling problem with distinct due-dates for operations. J Heuristics 27, 175–204 (2021). https://doi.org/10.1007/s10732-020-09458-6

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