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Single machine total completion time minimization scheduling with a time-dependent learning effect and deteriorating jobs

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  • Ji-Bo Wang
  • Ming-Zheng Wang
  • Ping Ji

Abstract

In this article, we consider a single machine scheduling problem with a time-dependent learning effect and deteriorating jobs. By the effects of time-dependent learning and deterioration, we mean that the job processing time is defined by a function of its starting time and total normal processing time of jobs in front of it in the sequence. The objective is to determine an optimal schedule so as to minimize the total completion time. This problem remains open for the case of −1 < a < 0, where a denotes the learning index; we show that an optimal schedule of the problem is V-shaped with respect to job normal processing times. Three heuristic algorithms utilising the V-shaped property are proposed, and computational experiments show that the last heuristic algorithm performs effectively and efficiently in obtaining near-optimal solutions.

Suggested Citation

  • Ji-Bo Wang & Ming-Zheng Wang & Ping Ji, 2012. "Single machine total completion time minimization scheduling with a time-dependent learning effect and deteriorating jobs," International Journal of Systems Science, Taylor & Francis Journals, vol. 43(5), pages 861-868.
    • Handle: RePEc:taf:tsysxx:v:43:y:2012:i:5:p:861-868
    DOI: 10.1080/00207721.2010.542837
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    Cited by:

    1. Pei, Jun & Pardalos, Panos M. & Liu, Xinbao & Fan, Wenjuan & Yang, Shanlin, 2015. "Serial batching scheduling of deteriorating jobs in a two-stage supply chain to minimize the makespan," European Journal of Operational Research, Elsevier, vol. 244(1), pages 13-25.
    2. Qian, Jin & Lin, Hexiang & Kong, Yufeng & Wang, Yuansong, 2020. "Tri-criteria single machine scheduling model with release times and learning factor," Applied Mathematics and Computation, Elsevier, vol. 387(C).
    3. Baoyu Liao & Xingming Wang & Xing Zhu & Shanlin Yang & Panos M. Pardalos, 2020. "Less is more approach for competing groups scheduling with different learning effects," Journal of Combinatorial Optimization, Springer, vol. 39(1), pages 33-54, January.

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