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Self-adaptive Length Genetic Algorithm for Urban Rerouting Problem

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Advances in Natural Computation (ICNC 2006)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4221))

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Abstract

Vehicle rerouting can reduce the travel cost in high-volume traffic network by real-time information. However, it is a computational challenge. A self-adaptive string length evolution strategy was presented so as to meet the inconstant intersection number in different potential routes. String length would be adjusted according to the intersection number. Simulation results showed it could work well in the urban rerouting problem.

The work is supported by National Natural Science Foundation of China (60134010) and Talent Recruitment Foundation of NUAA (S0398-071).

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Author information

Authors and Affiliations

  1. Collage of Civil Aviation, Nanjing University of Aeronautics & Astronautics, 210016, China

    Li Cao

  2. Department of Automatic Control, Northwestern Polytechnical University, 710072, China

    Zhongke Shi

  3. University of South Florida, FL, 33803, USA

    Li Cao & Paul Bao

Authors
  1. Li Cao
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  2. Zhongke Shi
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  3. Paul Bao
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Editor information

Editors and Affiliations

  1. Life Science Research Center, School of Electronic Engineering, Xidian University, 710071, Xi’an, Shaanxi, China

    Licheng Jiao

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

    Lipo Wang

  3. School of Electronic Engineering, Xidian Univ., 710071, Xi’an, P.R. China

    Xin-bo Gao

  4. College of Mathematics and Information Science, Hebei Normal University, 050016, Shijiazhuang, Hebei, P.R. China

    Jing Liu

  5. Multi-Agent Systems Lab,Department of Computer Science, University of Science and Technology of China, 230026, Hefei, China

    Feng Wu

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© 2006 Springer-Verlag Berlin Heidelberg

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Cao, L., Shi, Z., Bao, P. (2006). Self-adaptive Length Genetic Algorithm for Urban Rerouting Problem. In: Jiao, L., Wang, L., Gao, Xb., Liu, J., Wu, F. (eds) Advances in Natural Computation. ICNC 2006. Lecture Notes in Computer Science, vol 4221. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11881070_97

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  • DOI: https://doi.org/10.1007/11881070_97

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-45901-9

  • Online ISBN: 978-3-540-45902-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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