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New Mechanism of Combination Crossover Operators in Genetic Algorithm for Solving the Traveling Salesman Problem

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Knowledge and Systems Engineering

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 326))

Abstract

Traveling salesman problem (TSP) is a well-known in computing field. There are many researches to improve the genetic algorithm for solving TSP. In this paper, we propose two new crossover operators and new mechanism of combination crossover operators in genetic algorithm for solving TSP. We experimented on TSP instances from TSP-Lib and compared the results of proposed algorithm with genetic algorithm(GA), which used MSCX. Experimental results show that, our proposed algorithm is better than the GA using MSCX on the min, mean cost values.

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Author information

Authors and Affiliations

  1. Tay Bac University, Son La, Vietnam

    Pham Dinh Thanh

  2. Hanoi University of Science and Technology, Hanoi, Vietnam

    Huynh Thi Thanh Binh

  3. Le Quy Don Technical University, Hanoi, Vietnam

    Bui Thu Lam

Authors
  1. Pham Dinh Thanh
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  2. Huynh Thi Thanh Binh
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  3. Bui Thu Lam
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Editor information

Editors and Affiliations

  1. Faculty of Information Technology, VNU University of Engineering and Technology, Hanoi, Vietnam

    Viet-Ha Nguyen

  2. Faculty of Information Technology, VNU University of Engineering and Technology, Hanoi, Vietnam

    Anh-Cuong Le

  3. School of Knowledge Science, Japan Advanced Institute of Science and Technology, Nomi, Ishikawa, Japan

    Van-Nam Huynh

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© 2015 Springer International Publishing Switzerland

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Dinh Thanh, P., Thi Thanh Binh, H., Thu Lam, B. (2015). New Mechanism of Combination Crossover Operators in Genetic Algorithm for Solving the Traveling Salesman Problem. In: Nguyen, VH., Le, AC., Huynh, VN. (eds) Knowledge and Systems Engineering. Advances in Intelligent Systems and Computing, vol 326. Springer, Cham. https://doi.org/10.1007/978-3-319-11680-8_29

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  • DOI: https://doi.org/10.1007/978-3-319-11680-8_29

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-11679-2

  • Online ISBN: 978-3-319-11680-8

  • eBook Packages: EngineeringEngineering (R0)

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