Algorithms and Optimization Techniques for Solving TSP
A comparative study to test and evaluate the performance of three algorithms: Simulated Annealing, Ant Colony Optimization, and Genetic Algorithm by setting up analogous environments of n cities.
Abstract
The traveling salesman problem (TSP) is one of the most extensively studied optimization problems in the computer science and computational mathematics field given that there is yet an optimal solution for it to be discovered. This algorithmic issue requests the shortest possible route that visits each city precisely once and returns to its initial starting point if a list of n places and the distances between each pair are given. This paper conducts a comparative study to test and evaluate the performance of three algorithms: Simulated Annealing, Ant Colony Optimization, and Genetic Algorithm. With the traveling salesman problem classifying under NP-hard computational complexity, the proposed research work will examine the runtime as well as the shortest distance computed by each of these algorithms by setting up analogous environments of n cities.