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Genetic Algorithm for Mixed Chinese Postman Problem

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Advances in Computation and Intelligence (ISICA 2010)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6382))

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Abstract

Mixed Chinese Postman Problem (Mixed CPP) is a NP-Complete problem. This problem has many applications, including route optimization, analyzing interactive system and flow design. This paper presents a genetic algorithm to solve this problem, which has got a good result. Problem-specific genetic operators were designed to keep every individual in population is reasonable and to improve the exploration efficiency. Data experiments show the algorithm is efficient and is better than the existing approximation algorithms.

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Author information

Authors and Affiliations

  1. Computer School, Wuhan University, Wuhan, Hubei, China

    Hua Jiang & Lishan Kang

  2. Computer School, Donghu College, Wuhan University, Wuhan, Hubei, China

    Shuqi Zhang

  3. China Construction Bank Wuhan Audition Branch, Wuhan, China

    Fei Zhu

Authors
  1. Hua Jiang
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  2. Lishan Kang
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  3. Shuqi Zhang
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  4. Fei Zhu
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Editor information

Editors and Affiliations

  1. School of Computer Science, China University of Geosciences, 430074, Wuhan, Hubei, P.R. China

    Zhihua Cai

  2. School of Computer Science, China University of Geosciences, Wu-Han, China University of Geosciences, 430074, Wuhan, Hubei, P.R. China

    Chengyu Hu

  3. Computation Center, Wuhan University, 430072, Wuhan, Hubei, China

    Zhuo Kang

  4. School of Computer Science and Engineering, The University of Aizu, Tsuruga, Ikki-machi, 965-8580, Aizu-Wakamatsu City, Fukushima, Japan

    Yong Liu

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© 2010 Springer-Verlag Berlin Heidelberg

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Cite this paper

Jiang, H., Kang, L., Zhang, S., Zhu, F. (2010). Genetic Algorithm for Mixed Chinese Postman Problem. In: Cai, Z., Hu, C., Kang, Z., Liu, Y. (eds) Advances in Computation and Intelligence. ISICA 2010. Lecture Notes in Computer Science, vol 6382. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16493-4_20

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  • DOI: https://doi.org/10.1007/978-3-642-16493-4_20

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-16492-7

  • Online ISBN: 978-3-642-16493-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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