A Comparison of Ant Colony Optimization and Genetic Algorithm for Solving the Traveling Salesman Problem

Abstract

Every company in today’s world faces the constant challenge of cost reduction. For distribution and transport service providers, cost cutting appears to be the main operational goal. The successful companies seek to develop a optimal routes for their fleets to minimize the costs and guarantee a timely delivery of the goods.
With a growing informatization of the industrial world, it is worth considering the use of intelligent systems as a possible way of solving various types of decision problems, which in turn can contribute to the reduction of costs incurred by a company. Such systems enable multidimensional data analysis and to provide information useful in decision making.
The paper investigates the use of the genetic algorithm and the ants colony optimization algorithm as a solution to the travelling salesman problem. It has been shown that both methods provide satisfactory results in solving the problem under examination.