GPU-based parallel genetic approach to large-scale travelling salesman problem
In this paper, we propose an improved crossover method for genetic approach to travelling salesman problem (TSP). Because any feasible solution of TSP must be an ordered permutation, the validity of an offspring generated by the simple crossover where corresponding parts of genes or chromosomes of parents are exchanged. Therefore, researchers have proposed special crossover methods, and so far it is known that SCX is superior to other methods in the aspect of convergence speed and fitness of the genes. In this paper, we extend the SCX to have bidirectional and circular search properties in the construction of offsprings. We also devised an simple and effective index management so that the search for candidate nodes during the offspring construction can be performed in an efficient way. The proposed BCSCX shows the better convergence speed and even better solution than those of SCX in the empirical experiments.