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Application of Job Shop Based on Immune Genetic Algorithm

Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 297)

Abstract

Job Shop scheduling problem,as an important part of computer integrated manufacturing system engineering, is a classic NP-hard combinatorial optimization problem and has vital effect on production management and control system. In this paper, base on biological immune system’s antigen recognition, maintaining the diversity of antibodies and other features, a proposed improved genetic algorithm-the immune genetic algorithm is put forward, the algorithm will introduce the thinking of biological systems immune to the genetic algorithm, namely in use of first immune knowledge it structures inspection operator. By vaccination and immune selection, it not only retains the best individual groups but also ensures the diversity of individuals, thus avoiding the premature convergence of evolutionary search and improving convergence speed, meantime, an improved immune genetic algorithm, and adopting timely dynamic vaccination and the shut down criteria are given. Simulation results show that the algorithm is effective.

Keywords

Genetic Algorithm immune job shop NP-hard hypermutation 

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References

  1. 1.
    Goncalves, J.F.: European Journal of Operational Research, 77–95 (2005)Google Scholar
  2. 2.
    Li, W.: Proceedings of the United States Department of Energy Cyber Security Group 2004 Training Conference, pp. 24–27 (2004)Google Scholar
  3. 3.
    Alhazzaa, L.: King Saud University Computer Science Collage CSC590_Selected Topic (2002)Google Scholar
  4. 4.
    Stein, G.: ACM Southeast Regional Conference Proceedings of the 43rd Annual Southeast Regional Conference, vol. 2, pp. 136–141 (2005)Google Scholar
  5. 5.
    Liu, X.Y.: Master’s thesis, Project Management, Tianjin University (2008)Google Scholar
  6. 6.
    Wang, A.T.: Master’s thesis, Communication and Information System, Ocean University of China (2008)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.Software CollegeShenyang Normal UniversityShen YangChina

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