Magnetic Optimization Algorithm Approach For Travelling Salesman Problem

Lately, numerous nature inspired optimization techniques has been applied to combinatorial optimization problems, such as Travelling Salesman Problem. In this paper, we study the implementation of one of the nature inspired optimization techniques called Magnetic Optimization Algorithm in Travelling Salesman Problem. In this implementation, each magnetic agent or particle in Magnetic Optimization Algorithm represents a candidate solution of the Travelling Salesman Problem. The strength of the magnetic force between these particles is inversely proportion to the distance calculated by the Traveling Salesman Problem's solution they represented. Particles with higher magnetic force will attract other particles with relatively lower magnetic force, towards it. The process repeated until satisfying a stopping condition, and the solution with lowest distance is considered as the best-found solution. The performance of the proposed approach is benchmarked with a case study taken from a well-known test bank