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

In today’s society, everyone uses a vehicle for transportation, which results in a lot of air pollution, traffic, and time and fuel waste. It also causes driver unhappiness and costs billions of dollars in fuel use every year throughout the world. The dynamic and unpredictable nature of the organisation geography of vehicular situations, particularly in metropolitan zones, makes finding an acceptable solution for car clog a difficult task. The study’s goal is to determine the quickest path to reduce the time spent travelling. There are several factors to consider when optimising an ant colony. The problem of the travelling salesman has been solved using a variety of ways. The purpose of this literature review is to learn how ant colony optimization methods are utilised to solve the travelling salesman issue and increase performance according to the requirements. The behaviour of ants has been seen to aid in the optimization of the ant colony algorithm. Other ants follow the pheromone trail left by the ant while walking, and ants can identify the shortest way of travel by following the pheromone trail. Similarly, the ACO is employed in TSP, where the algorithm assists in only visiting each city once with the least amount of distance and time.

Author (S) Details

Dr. Priyanka P. Shinde
Government College of Engineering Karad, Karad, Maharashtra, India.

Varsha P. Desai
Department of Studies, V.P. Institute of Management Studies & Research, Sangli, Maharashtra, India.

Dr. Kavita S. Oza
Computer Science Department, Shivaji University, Kolhapur, Maharashtra, India.

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