Modified Genetic Algorithm for Traveling Salesman Problem
Zhaoxuan Yang, Pla Uni · Journal of PLA University of Science and Technology · 2004
Traditional genetic algorithms have low efficiency and tend to be trapped by local optimizations. An improvement is proposed to solve this problem. Elitism and 2-tournament selection are used to expand the selection of chromosomes, so that the ones with better fitness have more chances to be selected. Crossover operation adds the edge information of parents chromosomes. Crossover and multation probability are related to individual fitness, and this guaratees that chromosomes with better fitness can survive into the next generation. Two algorithms are implementd. Experiments show that the new algorithm improvs the efficiency of the traveling salesman problem.