Application of Ant Colony Optimization: An Approach towards Travelling Salesman Problem Resolution

Abstract

In today’s world everyone uses vehicle for the transportation this leads lots of air pollution, lots of traffic and wastage of time as well as wastage of fuel. It also leads driver dissatisfaction and costs billions of dollars every year in fuel utilization all over the world. Tracking down an appropriate answer for vehicle clog is an extensive test because of the dynamic and capricious nature of the organization geography of vehicular conditions, particularly in metropolitan regions. The objective of study is to find the shortest path to minimize the drawback of travelling. In the ant colony optimization, there are various techniques used to resolve the travelling salesman problem. The literature study of ant colony optimization algorithm is studied to find out how the ant colony algorithms used for solving the travelling salesman problem and improve the performance according to the requirements. The behavior of ant is observed to do improvements in the ant colony optimization algorithm. Ant leaves pheromone while traveling the other ants follows that pheromone trail and by trail of pheromone, ants can determine the shortest path of travelling. Similarly, the ACO is used in TSP in which the algorithm helps to visit each city only once with minimal distance and time.