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Applying K-means Clustering and Genetic Algorithm for Solving MTSP

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Bio-inspired Computing – Theories and Applications (BIC-TA 2016)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 682))

Abstract

In this paper, a new algorithm is designed to solve Multiple Traveling Salesman Problem (MTSP) that avoiding the path intersection among the traveling salesmen. There are three objectives in this problem including the shortest path of every salesman, the balance of each salesmans task and avoiding the crosses of each routes. We combine the K-means algorithm and genetic algorithm. K-means algorithm is designed to divide all points into several subsets and choose the start city for the genetic algorithm, and then using GA to process every subsets in parallel. This method not only achieve these multiple objectives, but also use much less time, since we have divided all the points into several parts and make them calculated at the same time.

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Acknowledgment

This work was supported by the National Natural Science Foundation of China (Grant Nos. 61472293, 61502012, 60974112 and 91130034), Natural Science Foundation of Hubei Province (2015CFB335), and the Beijing Natural Science Foundation (4164096).

Author information

Authors and Affiliations

  1. School of Computer Science, Wuhan University of Science and Technology, Wuhan, 430081, China

    Zhanqing Lu, Kai Zhang & Juanjuan He

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

    Kai Zhang & Juanjuan He

  3. School of Information Engineering, China University of Geosciences, Beijing, 100083, China

    Yunyun Niu

Authors
  1. Zhanqing Lu
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  2. Kai Zhang
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  3. Juanjuan He
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  4. Yunyun Niu
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Corresponding author

Correspondence to Juanjuan He .

Editor information

Editors and Affiliations

  1. Xidian University , Xi’an, China

    Maoguo Gong

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

    Linqiang Pan

  3. China University of Petroleum, Qingdao, China

    Tao Song

  4. Southwest Jiaotong University , Chengdu, China

    Gexiang Zhang

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© 2016 Springer Nature Singapore Pte Ltd.

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Lu, Z., Zhang, K., He, J., Niu, Y. (2016). Applying K-means Clustering and Genetic Algorithm for Solving MTSP. In: Gong, M., Pan, L., Song, T., Zhang, G. (eds) Bio-inspired Computing – Theories and Applications. BIC-TA 2016. Communications in Computer and Information Science, vol 682. Springer, Singapore. https://doi.org/10.1007/978-981-10-3614-9_34

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  • DOI: https://doi.org/10.1007/978-981-10-3614-9_34

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-3613-2

  • Online ISBN: 978-981-10-3614-9

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