A Modified and Enhanced Ant Colony Optimization Algorithm for Traveling Salesman Problem

  • Leila Eskandari
  • Ahmad Jafarian
  • Parastoo Rahimloo
  • Dumitru Baleanu
Part of the Nonlinear Systems and Complexity book series (NSCH, volume 23)


In this paper an effective modification has been performed on the Ant Colony Optimization algorithm and used for solving traveling salesman problem (TSP). The traveling salesman problem is one of the famous and important problems and it has been used in the algorithms to analyze its performance in solving the discreet problems. The modified and enhanced ACO has been used for solving this problem and it is called MEACO. In MEACO the modification has been performed by taking effect of mutation on the global best and personal best of each ant. The personal best is stored for each ant same as the PSO algorithm. Original ACO for discrete problems mostly trap in the local solutions, but the proposed method has been designed to cover this deficiency and make it more suitable for optimization of discrete problems. The experiment on the set of benchmark problems for Traveling salesman was performed and obtained results showed that MEACO is an effective method in finding the path for TSP.


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© Springer International Publishing AG, part of Springer Nature 2019

Authors and Affiliations

  • Leila Eskandari
    • 1
  • Ahmad Jafarian
    • 2
  • Parastoo Rahimloo
    • 2
  • Dumitru Baleanu
    • 3
  1. 1.Department of Computer EngineeringUrmia Branch, Islamic Azad UniversityUrmiaIran
  2. 2.Department of MathematicsUrmia Branch, Islamic Azad UniversityUrmiaIran
  3. 3.Department of MathematicsÇankaya UniversityAnkaraTurkey

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