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A new model for single machine scheduling with uncertain processing time

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Abstract

Uncertain single machine scheduling problem for batches of jobs is an important issue for manufacturing systems. In this paper, we use uncertainty theory to study the single machine scheduling problem with deadlines where the processing times are described by uncertain variables with known uncertainty distributions. A new model for this problem is built to maximize expected total weight of batches of jobs. Then the model is transformed into a deterministic integer programming model by using the operational law for inverse uncertainty distributions. In addition, a property of the transformed model is provided and an algorithm is designed to solve this problem. Finally, a numerical example is given to illustrate the effectiveness of the model and the proposed algorithm.

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Acknowledgments

This work was supported by National Natural Science Foundation of China Grant Nos. 11471152 and 61273044, and Fuzzy Logic Systems Institute, Japan (JSPS-the Grant-in-Aid for Scientific Research C; No. 24510219).

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Authors and Affiliations

  1. School of Mathematical Sciences, Liaocheng University, Liaocheng, 252059, China

    Kai Hu & Xingfang Zhang

  2. Tokyo University of Science, Tokyo, Japan

    Mitsuo Gen

  3. Japan and Fuzzy Logic Systems Institute, Iizuka, Japan

    Mitsuo Gen

  4. Division of Computer and Information Engineering, Dongseo University, Busan, South Korea

    Jungbok Jo

Authors
  1. Kai Hu
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  2. Xingfang Zhang
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  3. Mitsuo Gen
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  4. Jungbok Jo
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Correspondence to Xingfang Zhang.

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Hu, K., Zhang, X., Gen, M. et al. A new model for single machine scheduling with uncertain processing time. J Intell Manuf 28, 717–725 (2017). https://doi.org/10.1007/s10845-015-1033-9

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  • DOI: https://doi.org/10.1007/s10845-015-1033-9

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