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Resource-dependent scheduling with deteriorating jobs and learning effects on unrelated parallel machine

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Abstract

The focus of this paper is to analyze unrelated parallel-machine resource allocation scheduling problem with learning effect and deteriorating jobs. The goal is to find the optimal sequence of jobs and the optimal resource allocation separately for minimizing the cost function including the total load, the total completion time, the total absolute deviation of completion time and the total resource cost. We show that the problem is polynomial time solvable if the number of machines is a given constant.

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Acknowledgments

This research was supported by the Science and Technology Development Project of Jilin Province of China (Grant No. 20140520057JH), The Hong Kong Polytechnic University (Project 4-BCBJ) and the National Natural Science Foundation of China (Grant No. 71471120).

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Authors and Affiliations

  1. College of Mathematics, Jilin Normal University, Siping, 136000, Jilin, China

    Yuan-Yuan Lu

  2. School of Government, Beijing Normal University, Beijing, 100875, China

    Jian Jin

  3. Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong

    Ping Ji

  4. School of Science, Shenyang Aerospace University, Shenyang, 110136, China

    Ji-Bo Wang

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  1. Yuan-Yuan Lu
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  2. Jian Jin
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  3. Ping Ji
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  4. Ji-Bo Wang
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Correspondence to Yuan-Yuan Lu.

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Lu, YY., Jin, J., Ji, P. et al. Resource-dependent scheduling with deteriorating jobs and learning effects on unrelated parallel machine. Neural Comput & Applic 27, 1993–2000 (2016). https://doi.org/10.1007/s00521-015-1993-x

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  • DOI: https://doi.org/10.1007/s00521-015-1993-x

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