Analyzing travelling salesman problem with new parameters using Ant Colony Optimization

Abstract: Travelling salesman problem is studied in the field of combinatorial optimization. TSP being heuristic algorithm tries to find minimum distance between given set of cities by traversing each of these cities only once except the starting city. A lot of techniques have been developed to solve TSP like Ant Colony optimization, Genetic algorithms, neural networks etc. Ant Colony optimization (ACO) being a heuristic algorithm attempts to find optimum solution by mimicking ants finding food as a group. Ants release pheromones on their path, concentration of which suggests shortest path to food. Models have been developed to solve ACO with fixed parameters. This paper attempts to analyze and find the best value for the set of parameters like "Exponential Weight", "Heuristic exponential Weight", "Evaporation Rate� for this solution based on no. of iteration and minimum distance traversed.

Keywords: Ant Colony Optimization algorithm, Evaporation Rate, Genetic Algorithm, Travelling Salesman Problem, Heuristic exponential weight.