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A Novel Cultural Algorithm Based on Differential Evolution for Hybrid Flow Shop Scheduling Problems with Fuzzy Processing Time

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Book cover Integrated Uncertainty in Knowledge Modelling and Decision Making (IUKM 2011)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7027))

Abstract

Considering the imprecise or fuzzy nature of the data in real-world problems, this paper proposes a novel cultural algorithm based on differential evolution (CADE) to solve the hybrid flow shop scheduling problems with fuzzy processing time(FHFSSP). The mutation and crossover operations of differential evolution (DE) are introduced into cultural algorithm (CA) to enhance the performance of traditional CA. Experimental results demonstrate that the proposed CADE method is more effective than CA, particle swarm optimization (PSO) and quantum evolution algorithm (QA) when solving FHFSSP.

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Author information

Authors and Affiliations

  1. Shanghai Key Laboratory of Power Station, School of Mechatronic Engineering and Automation, Shanghai University, Shanghai, China

    Qun Niu, Tingting Zeng & Zhuo Zhou

Authors
  1. Qun Niu
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  2. Tingting Zeng
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  3. Zhuo Zhou
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Editor information

Editors and Affiliations

  1. College of Computer Science, Zhejiang University, 310027, Hangzhou, Zhejiang Province, P.R. China

    Yongchuan Tang

  2. Japan Advanced Institute of Science and Technology (JAIST), 923-1292, Tatsunokuchi, Ishikawa, Japan

    Van-Nam Huynh

  3. Artificial Intelligence Group, Engineering Mathematics Department, University of Bristol, BS8 1TR, UK

    Jonathan Lawry

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© 2011 Springer-Verlag Berlin Heidelberg

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Niu, Q., Zeng, T., Zhou, Z. (2011). A Novel Cultural Algorithm Based on Differential Evolution for Hybrid Flow Shop Scheduling Problems with Fuzzy Processing Time. In: Tang, Y., Huynh, VN., Lawry, J. (eds) Integrated Uncertainty in Knowledge Modelling and Decision Making. IUKM 2011. Lecture Notes in Computer Science(), vol 7027. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24918-1_15

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  • DOI: https://doi.org/10.1007/978-3-642-24918-1_15

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-24917-4

  • Online ISBN: 978-3-642-24918-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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