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An uncertain multi-objective programming model for machine scheduling problem

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Abstract

This paper discusses a parallel machine scheduling problem in which the processing times of jobs and the release dates are independent uncertain variables with known uncertainty distributions. An uncertain programming model with multiple objectives is obtained, whose first objective is to minimize the maximum completion time or makespan, and second objective is to minimize the maximum tardiness time. A genetic algorithm is employed to solve the proposed uncertain machine scheduling model, and its efficiency is illustrated by some numerical experiments.

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Acknowledgments

This work is supported by Natural Science Foundation of Shandong Province (ZR2014GL002).

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Authors and Affiliations

  1. School of Information Engineering, Shandong Youth University of Political Science, Jinan, 250103, China

    Yufu Ning, Xiumei Chen, Zhiyong Wang & Xiangying Li

  2. Key Laboratory of Information Security and Intelligent Control in Universities of Shandong, Jinan, 250103, China

    Yufu Ning, Xiumei Chen, Zhiyong Wang & Xiangying Li

Authors
  1. Yufu Ning
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  2. Xiumei Chen
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  3. Zhiyong Wang
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  4. Xiangying Li
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Correspondence to Yufu Ning.

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Ning, Y., Chen, X., Wang, Z. et al. An uncertain multi-objective programming model for machine scheduling problem. Int. J. Mach. Learn. & Cyber. 8, 1493–1500 (2017). https://doi.org/10.1007/s13042-016-0522-2

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  • DOI: https://doi.org/10.1007/s13042-016-0522-2

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