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International Conference on Bio-Inspired Computing: Theories and Applications

BIC-TA 2018: Bio-inspired Computing: Theories and Applications pp 186–197Cite as

An Efficient Genetic Algorithm for Solving Constraint Shortest Path Problem Through Specified Vertices

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 951))

Abstract

Finding a constraint shortest path which passes through a set of specified vertices is very important for many research areas, such as intelligent transportation systems, emergency rescue, and military planning. In this paper, we propose an efficient genetic algorithm for solving the constraint shortest path problem. Firstly, the Dijkstra algorithm is used to calculate the shortest distance between any two specified vertices. The optimal solution change from the original problem into the Hamilton path problem with the specified vertices. Because the number of specified vertices is much less than the number of vertices for the whole road network, the search space would be reduced exponentially. Secondly, the genetic algorithm is adopted to search for the optimal solution of the Hamilton path problem. Thirdly our algorithm should detect and eliminate the cycle path. Finally, the performance of our algorithm is evaluated by some real-life city road networks and some randomly generated road networks. The computational results show that our algorithm can find the constraint shortest path efficiently and effectively.

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Acknowledgments

This work was supported by the National Natural Science Foundation of China (Grant Nos. 61472293 and 61702383). Research Project of Hubei Provincial Department of Education (Grant No. 2016238).

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Authors and Affiliations

  1. School of Computer Science, Wuhan University of Science and Technology, Wuhan, 430081, People’s Republic of China

    Zhang Kai, Shao Yunfeng, Zhang Zhaozong & Hu Wei

  2. Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System, Wuhan, 430081, China

    Zhang Kai

Authors
  1. Zhang Kai
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  2. Shao Yunfeng
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  3. Zhang Zhaozong
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  4. Hu Wei
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Corresponding author

Correspondence to Hu Wei .

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Editors and Affiliations

  1. Beijing University of Posts and Telecommunications, Beijing, China

    Jianyong Qiao

  2. Beijing University of Posts and Telecommunications, Beijing, China

    Xinchao Zhao

  3. Huazhong University of Science and Technology, Wuhan, China

    Linqiang Pan

  4. Beijing University of Posts and Telecommunications, Beijing, China

    Xingquan Zuo

  5. Anhui University, Hefei, China

    Xingyi Zhang

  6. City University of Hong Kong, Kowloon, Hong Kong

    Qingfu Zhang

  7. Beijing University of Posts and Telecommunications, Beijing, China

    Shanguo Huang

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© 2018 Springer Nature Singapore Pte Ltd.

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Kai, Z., Yunfeng, S., Zhaozong, Z., Wei, H. (2018). An Efficient Genetic Algorithm for Solving Constraint Shortest Path Problem Through Specified Vertices. In: Qiao, J., et al. Bio-inspired Computing: Theories and Applications. BIC-TA 2018. Communications in Computer and Information Science, vol 951. Springer, Singapore. https://doi.org/10.1007/978-981-13-2826-8_17

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  • DOI: https://doi.org/10.1007/978-981-13-2826-8_17

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-2825-1

  • Online ISBN: 978-981-13-2826-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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