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International Conference in Swarm Intelligence

ICSI 2012: Advances in Swarm Intelligence pp 383–390Cite as

Discover Scheduling Strategies with Gene Expression Programming for Dynamic Flexible Job Shop Scheduling Problem

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7332))

Abstract

In this paper, an intelligent approach based on gene expression programming (GEP) is proposed to discover scheduling strategies for dynamic flexible job shop scheduling problem (DFJSP). In the approach, an indirect encoding and decoding scheme is designed in which the concept of automatically defined functions (ADF) is introduced. In the evaluation of the proposed GEP-based approach, simulation experiments are conducted with respect to the objective of minimizing mean tardiness. The results show that GEP-based approach can automatically find more efficient scheduling strategies for DFJSP under a big range of processing conditions.

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Author information

Authors and Affiliations

  1. School of Mechanical & Electronic Engineering, Shanghai Second Polytechnic University, Jinhai Road 2360, Pudong District, Shanghai, 201209, People’s Republic of China

    Li Nie, Yuewei Bai, Xiaogang Wang & Kai Liu

Authors
  1. Li Nie
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  2. Yuewei Bai
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  3. Xiaogang Wang
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  4. Kai Liu
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Editor information

Editors and Affiliations

  1. Key Laboratory of Machine Perception (MOE), Peking University, Department of Machine Intelligence, School of Electronics Engineering and Computer Science, Peking University, 100871, Beijing, China

    Ying Tan

  2. Department of Electrical and Electronic Engineering, Xi’an Jiaotong-Liverpool University, Suzhou, China

    Yuhui Shi

  3. Shenzhen City Key Laboratory of Embedded System Design, College of Computer Science and Software Engineering, Shenzhen University, 518060, Shenzhen, China

    Zhen Ji

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© 2012 Springer-Verlag Berlin Heidelberg

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Nie, L., Bai, Y., Wang, X., Liu, K. (2012). Discover Scheduling Strategies with Gene Expression Programming for Dynamic Flexible Job Shop Scheduling Problem. In: Tan, Y., Shi, Y., Ji, Z. (eds) Advances in Swarm Intelligence. ICSI 2012. Lecture Notes in Computer Science, vol 7332. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31020-1_45

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  • DOI: https://doi.org/10.1007/978-3-642-31020-1_45

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-31019-5

  • Online ISBN: 978-3-642-31020-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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