Improved simulated annealing algorithm and genetic algorithm for TSP.
The characteristics of genetic algorithm and simulated annealing algorithm are compared, it elaborates the necessity of the combination of genetic algorithm and simulated annealing algorithm. An improved simulated annealing and genetic algo-rithm for solving TSP is proposed. The global random searching ability of genetic algorithm makes up the question of the simu-lated annealing algorithm that easy to fall into the local optimal solution. The crossover method of genetic algorithm is changed, the parent chromosomes and offspring chromosomes are crossed, it solves the problems of traditional genetic algorithm“prema-ture”. It proposes new solution generation mechanisms and improved algorithm for that the simulated annealing algorithm con-verges slowly, the method improves the speed of convergence of the algorithm. Experimental test results show that the new algo-rithm has faster convergence and better stability.
国家科技期刊平台
NSTL
万方数据
维普
