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Solving Job-Shop Scheduling Problems by a Novel Artificial Immune System

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AI 2005: Advances in Artificial Intelligence (AI 2005)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3809))

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Abstract

The optimization of job-shop scheduling is very important because of its theoretical and practical significance. This paper proposes an efficient scheduling method based on artificial immune systems. In the proposed method, the initial population is generated by a proposed scheduling initialization algorithm based on the G&T algorithm, and the models of the vaccination and receptor editing are designed to improve the immune performance. The approach is tested on a set of standard instances taken from the existing standard library. The simulation results validate the effectiveness of the proposed algorithm.

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References

  1. Beasley, J.E.: OR-Library: Distributing Test Problems by Electronic Mail. Journal of the Operations Research Society 41(11), 1069–1072 (1990)

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  2. Binato, S., Hery, W.J., Loewenstern, D.M., Resende, M.G.C.: A GRASP for Job Shop Scheduling. In: Essays and Surveys in Metaheuristics, pp. 59–80. Kluwer Academic Publishers, Boston (2001)

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Author information

Authors and Affiliations

  1. College of Computer Science, Jilin University, Key Laboratory of Symbol Computation and Knowledge Engineering of the Ministry of Education, Changchun, 130012, China

    Hong-Wei Ge, Liang Sun & Yan-Chun Liang

Authors
  1. Hong-Wei Ge
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  2. Liang Sun
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  3. Yan-Chun Liang
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Editor information

Editors and Affiliations

  1. Guangxi Normal University, College of CS and IT, Guilin, China, and University of Technology, Faculty of Engineering and Information Technology, Sydney, Australia

    Shichao Zhang

  2. Department of Electrical and Computer Systems Engineering, Monash University, 3800, Melbourne, Victoria, Australia

    Ray Jarvis

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© 2005 Springer-Verlag Berlin Heidelberg

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Ge, HW., Sun, L., Liang, YC. (2005). Solving Job-Shop Scheduling Problems by a Novel Artificial Immune System. In: Zhang, S., Jarvis, R. (eds) AI 2005: Advances in Artificial Intelligence. AI 2005. Lecture Notes in Computer Science(), vol 3809. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11589990_92

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  • DOI: https://doi.org/10.1007/11589990_92

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-30462-3

  • Online ISBN: 978-3-540-31652-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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