STM Journals Peer-reviewed research from Consortium e-Learning Network

Journal of Image Processing & Pattern Recognition Progress

A Survey on Ant Colony Optimization Algorithm for Travelling Salesman Problem

  1. Ranjeet Savita
  2. Pankaj Sharma
  3. Manish Gupta

Abstract

The ant colony optimization algorithm, abbreviated as ACO, is a meta-heuristic optimization algorithm which is based on the probability for solving different computational problems such as travelling salesman problem (TSP), job scheduling problem, vehicle routing problem etc. This algorithm is a member of ant colony algorithms family in swarm intelligence methods, which is based on the foraging behaviour of real ants. This paper presents a review on a variety of modified versions of ant colony optimization algorithms for solving travelling salesman problem. This work is helpful for a variety of researchers to solve TSP problem using a variety of modified versions of ACO algorithms.
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