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Adaptive Immune Algorithm for Solving Job-Shop Scheduling Problem

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Advances in Natural Computation (ICNC 2005)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3611))

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Abstract

Based on the information processing mechanism of immune system in biotic science, the process of the vaccination was analyzed. Then a new approach of immune algorithm problems for job-shop scheduling was proposed. This method can make self-adjustment of the immune responses along with the cultivation period of antibodies, and accelerate or suppress the generation of antibodies. Furthermore, it can gradually enhance recovery ability of the system, and find the optimal solution with more efficiency. Simulation results show that it is an effective approach.

Foundation item: this research is supported by the National Natural Science Foundation of China (NSFC Grant No.60374056 and 60405009).

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Author information

Authors and Affiliations

  1. Information Engineering Institute, Zhejiang University of Technology, Hangzhou, 310014, P.R. China

    Xinli Xu, Wanliang Wang & Qiu Guan

Authors
  1. Xinli Xu
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  2. Wanliang Wang
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  3. Qiu Guan
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Editor information

Editors and Affiliations

  1. School of Electrical and Electronic Engineering, Nanyang Technological University, Block S1, Nanyang Avenue, 639798, Singapore

    Lipo Wang

  2. School of Software, Sun Yat-Sen University, 510275, Guangzhou, China

    Ke Chen

  3. School of Computer Engineering, Nanyang Technological University, BLK N4, 2b-39, Nanyang Avenue, 639798, Singapore

    Yew Soon Ong

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© 2005 Springer-Verlag Berlin Heidelberg

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Xu, X., Wang, W., Guan, Q. (2005). Adaptive Immune Algorithm for Solving Job-Shop Scheduling Problem. In: Wang, L., Chen, K., Ong, Y.S. (eds) Advances in Natural Computation. ICNC 2005. Lecture Notes in Computer Science, vol 3611. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11539117_111

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  • DOI: https://doi.org/10.1007/11539117_111

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-28325-6

  • Online ISBN: 978-3-540-31858-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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