An Artificial Immune System Algorithm for Solving Traveling Salesman Problem

rAbstract: The last few decades have witnessed a progressive interest toward biologically inspired algorithms, like neural networks, genetic algorithms and now immune systems in solving real problems. Based on its fascinating capabilities, immune systems recently have been used in designing computational techniques. In this paper, a new and efficient artificial immune system algorithm based on clonal selection for solving the Traveling Salesman Problem, TSP, is proposed. In the design of the algorithm, enough attention is paid to the characteristics of the TSP solution space and vaccination. The performance of the proposed algorithm is much better than the previous application of artificial immune system to the TSP and is comparable with the results of other Metaheuristic methods. These results reveal the great potentials of AIS in solving NP-Hard problems like TSP and its related problems.

Keywords:

Artificial Immune System , Clonal Selection , Traveling Salesman Problem , MetaheuristicMethods