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Solving Fuzzy Job Shop Scheduling Problem Based on Interval Number Theory

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Proceedings of the 2012 International Conference on Information Technology and Software Engineering

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 211))

Abstract

This article discusses the job shop scheduling problem with fuzzy processing time and fuzzy deadline by using interval number theory, which is an efficient method to denote imprecise parameter. Firstly, we convert the original problem to constraint satisfaction problem (CSP) with the assumption that agreement index (AI) is a main optimization objective. Then, the particle swarm optimization (PSO) is merged with genetic algorithm (GA), i.e., an improved particle swarm optimization (IPSO) being used to solve the problem. Finally, the effectiveness of this algorithm is verified by large number of experiments.

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Author information

Authors and Affiliations

  1. Science and Technology on Information Systems Engineering Laboratory, Nation University of defense technology, Changsha, China

    Chuan He, Dishan Qiu & Hao Guo

Authors
  1. Chuan He
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  2. Dishan Qiu
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  3. Hao Guo
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Corresponding author

Correspondence to Chuan He .

Editor information

Editors and Affiliations

  1. Beijing Jiaotong University, Beijing, China, People's Republic

    Wei Lu

  2. Beijing Jiaotong University, Beijing, China, People's Republic

    Guoqiang Cai

  3. Beijing Jiaotong University, Beijing, China, People's Republic

    Weibin Liu

  4. Beijing Jiaotong University, Beijing, China, People's Republic

    Weiwei Xing

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He, C., Qiu, D., Guo, H. (2013). Solving Fuzzy Job Shop Scheduling Problem Based on Interval Number Theory. In: Lu, W., Cai, G., Liu, W., Xing, W. (eds) Proceedings of the 2012 International Conference on Information Technology and Software Engineering. Lecture Notes in Electrical Engineering, vol 211. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34522-7_42

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  • DOI: https://doi.org/10.1007/978-3-642-34522-7_42

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-34521-0

  • Online ISBN: 978-3-642-34522-7

  • eBook Packages: EngineeringEngineering (R0)

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