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Iterated population-based VND algorithms for single-machine scheduling with sequence-dependent setup times

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Abstract

This paper investigates the problem of single-machine scheduling with sequence-dependent setup times for minimizing the total weighted tardiness of jobs. Because the problem is non-deterministic polynomial-time hard (NP-hard), an iterated population-based variable neighborhood descent (IPBVND) search algorithm is proposed as the solution. The proposed algorithm first generates the initial population. Then, a novel member updated method is proposed to generate a solution for the IPBVND algorithm at each iteration. Finally, a VND algorithm with a series of block-based insertion neighborhood structures and a greedy local search are presented to improve the solution quality. The computational experiments were made on a set of benchmark problems, and the results demonstrated the effectiveness of the proposed algorithm.

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Acknowledgements

This paper was supported in part by the Ministry of Science and Technology, Taiwan, ROC, under the contract NSC 101-2221-E-147 -001. The authors are grateful to the anonymous referees for their constructive comments that have greatly improved the presentation of this paper.

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  1. Department of Accounting Information, Takming University of Science and Technology, No.56, Sec.1, Huanshan Rd., Neihu District, Taipei City, 11451, Taiwan, ROC

    Chun-Lung Chen

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  1. Chun-Lung Chen
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Correspondence to Chun-Lung Chen.

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Communicated by V. Loia.

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Chen, CL. Iterated population-based VND algorithms for single-machine scheduling with sequence-dependent setup times. Soft Comput 23, 3627–3641 (2019). https://doi.org/10.1007/s00500-018-3014-3

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