Genetic algorithm and a double-chromosome implementation to the traveling salesman problem

Abstract

The variety of methods used to solve the traveling salesman problem attests to the fact that the problem is still vibrant and of concern to researchers in this area. For problems with a large search space, similar to the traveling salesman problem, evolutionary algorithms such as genetic algorithm are very powerful and can be used to obtain optimized solutions. However, the challenge in applying a genetic algorithm to the traveling salesman problem is the choice of appropriate operators that could produce legal tours. In the literature, additional repair algorithms have been introduced and employed and the offspring produced by these genetic algorithm operators are modified to ensure that the generated chromosomes represent legal tours. Rather than sticking to repair algorithms, a double-chromosome approach is proposed in this article. The proposed method can be employed to optimize problems similar to the traveling salesman problem. The double-chromosome approach has been tested with a variety of traveling salesman problems, and the results indicated that the proposed method has a high rate of convergence toward the shortest tour.