A Comparitive Study of Nearest Neighbour Algorithm and Genetic Algorithm in Solving Travelling Salesman Problem

---------------------------------------------------------------------***--------------------------------------------------------------------Abstract In this paper, we have used two algorithms, i.e. the Nearest Neighbor algorithm and Genetic Algorithm to solve the Travelling Salesman problem. The Travelling Salesman problem is a widely studied problem in computational mathematics. In the Travelling Salesman problem, a salesman has to visit all the cities first and then move to the same city from where it has started its whole journey. One of the concerns here with this problem, here is that the salesman cannot visit a single city twice. There are several optimization techniques such as ant colony optimization, particle swarm optimization, genetic algorithm, nearest neighbor algorithm, etc. out of which we have solved Travelling salesman problem using a Genetic algorithm and Nearest neighbor algorithm. In our paper, we have shown that for the same group of cities plotted at different location, Genetic Algorithm has given significantly better results than Nearest Neighbor Algorithm