摘要
在遗传操作算法中通常是随机选择交叉和变异的基因位置。基于蚁群信息素和选择基因的概率,本文提出了一种选择基因的方法以提升局部最优化的性能和加速算法的收敛。通过求解旅行商问题(TSP)的仿真实验,表明了这种方法的有效性。
It is a normal way to randomly select crossover and mutation gene locus in genetic operating. In this paper, based on the pheromone of Ant Colony and the probability of selecting gene, a method to select gene is presented to raise the performance of local optimization and the speed of the algorithm convergence. The efficiency of the method has been shown by simulative experiments solving the Traveling Salesman Problems （TSP）.
出处
《计算机科学》
CSCD
北大核心
2007年第6期170-173,共4页
Computer Science
关键词
遗传算法
蚁群算法
全局最优化
信息表
旅行商问题(TSP)
Genetic algorithms, Ant colony algorithm, Global optimization, Pheromone, Traveling salesman problems （TSP）
