Comparative analysis of Three Metaheuristics for Solving the Travelling Salesman Problem

Authors

  • Safaa Bouzidi Dept. of Computer Science Faculty of Science, ChouaibDouakkali University El Jadida, Morocco
  • Moahmmed Essaid Riffi Dept. of Computer Science Faculty of science, ChouaibDouakkali University El Jadida, Morocco
  • Abdelhamid Bouzidi Dept. of Computer Science Faculty of Science, ChouaibDouakkali University El Jadida, Morocco

DOI:

https://doi.org/10.14738/tmlai.54.3211

Keywords:

Metaheuristic, Cat Swarm Optimization, Bat-inspired algorithm, Cuckoo Search, Travelling salesman problem, NP-hard

Abstract

this research paper aims to do a comparative study of three recent optimization metaheuristic approaches that had been applied to solve the NP-hard optimization problem called the travelling salesman problem. The three recent metaheuristics in study are cuckoo search algorithm, cat swarm optimization algorithm and bat-inspired algorithm.  To compare the performances of these methods, the three metaheuristics are applied to solve some benchmark instances of TSPLIB. The obtained results are collected and the error percentage is calculated. The discussion, will present which method is more efficient to solve the real application based on the travelling salesman problem.

 

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Published

2017-09-01

How to Cite

Bouzidi, S., Essaid Riffi, M., & Bouzidi, A. (2017). Comparative analysis of Three Metaheuristics for Solving the Travelling Salesman Problem. Transactions on Machine Learning and Artificial Intelligence, 5(4). https://doi.org/10.14738/tmlai.54.3211

Issue

Section

Special Issue : 1st International Conference on Affective computing, Machine Learning and Intelligent Systems