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Application of Metaheuristic Algorithms and Their Combinations to Travelling Salesman Problem

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Intelligent Computing and Optimization (ICO 2023)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 852))

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Abstract

This paper presents four classical metaheuristic algorithms: Genetic Algorithm (GA), Ant Colony Optimization (ACO), Simulated Annealing (SA), and Tabu Search (TS) for solving the Travelling Salesman Problem (TSP). In addition, this paper introduces two novel hybrid approaches, (SAACO) based on Ant Colony Optimization and Simulated Annealing, and (TSACO) based on Ant Colony Optimization and Tabu Search. To compare the efficiency of the considered algorithms and to verify the effectiveness of the novel hybrid algorithms, this paper uses ten well-known benchmark instances from TSPLIB; the instances are of variable difficulty and size, ranging from 70 to 783 nodes with different node topologies. Assessment criteria involve computational time, fitness value, convergence speed, and robustness of algorithms. The experimental results show that hybrid algorithms overcome the limitations of individual algorithms, namely the slow convergence and local optima. Moreover, when applied solely, hybrid algorithms achieve better fitness values than GA, ACO, and TS in most simulations.

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Authors and Affiliations

  1. Department of Computer Science, Wenzhou-Kean University, Wenzhou, China

    Yinhao Liu, Xu Chen & Omar Dib

Authors
  1. Yinhao Liu
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  2. Xu Chen
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  3. Omar Dib
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Corresponding author

Correspondence to Omar Dib .

Editor information

Editors and Affiliations

  1. Faculty of Electrical and Electronics Engineering, Modeling Evolutionary Algorithms Simulation and Artificial Intelligence, Ton Duc Thang University, Ho Chi Minh City, Vietnam

    Pandian Vasant

  2. Department of Computer Science, Chittagong University of Engineering and Technology, Chittagong, Bangladesh

    Mohammad Shamsul Arefin

  3. Laboratory of Non-traditional Energy Systems, Department of Theoretical and Applied Mechanics, Federal Scientific Agroengineering Center VIM, Russian University of Transport, Moscow, Russia

    Vladimir Panchenko

  4. Department of Computer Science, UOW Malaysia KDU Penang University College, George Town, Malaysia

    J. Joshua Thomas

  5. School of Economics and Decision Sciences, North West University, Mmabatho, South Africa

    Elias Munapo

  6. Faculty of Engineering Management, Poznań University of Technology, Poznan, Poland

    Gerhard-Wilhelm Weber

  7. Facultad de Ciencias Económicas y Empresariales, School of Economic and Business Sciences, Universidad Panamericana, Mexico City, Mexico

    Roman Rodriguez-Aguilar

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Liu, Y., Chen, X., Dib, O. (2023). Application of Metaheuristic Algorithms and Their Combinations to Travelling Salesman Problem. In: Vasant, P., et al. Intelligent Computing and Optimization. ICO 2023. Lecture Notes in Networks and Systems, vol 852. Springer, Cham. https://doi.org/10.1007/978-3-031-50330-6_1

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