A Novel Immunity-Growth Genetic Algorithm for Traveling Salesman Problem

A novel genetic algorithm based on immunity and growth for the traveling salesman problem is presented in the paper. To start with, a reversal exchange crossover and mutation operator is proposed to preserve the good sub tours and to make individuals various. Next, a new immune operator is proposed to restrain individuals´ degeneracy. In addition, a novel growth operator is proposed to obtain the optimal solution with more chances. Finally, we test the convergent rate of the algorithm and the best solution obtained by the algorithm after some generators. Experimental results show that the algorithm is feasible and effective.