Different population-based algorithms for Travelling Salesman Problem: A Review Paper

Abstract

In this review paper, travelling salesman problem (TSP) is used as a domain. TSP is widely used to test new heuristics and is a well-known classical NP-complete combinatorial optimization problem in operation research area. From different fields such as artificial intelligence, physics, operations research etc. this problem has attracted many researchers. TSP has been studied thoroughly in late years and many algorithms have been developed. To address this problem using classical methods many attempts had been made such as integer programming and graph theory algorithms. In TSP the rules are very simple. TSP states that the nodes that must be visited once should not be visited again. TSP has huge search space. To find the optimal solution is very difficult. In this paper, a survey and comparative analysis are done for better results in TSP. The basisof the literature survey identify some research gaps on which further work can be done. The comparative analysis is done on the basis of contrasting parameters by comparing the differentpopulation-based algorithms.