摘要
遗传算法具有较强的全局搜索能力,但容易陷入局部最优.把模拟退火算法的思想融入到遗传算法中,在选择、交叉和变异的过程中加入退火过程,并使用改进后的算法求解行程规划问题,实验结果证明设计的算法是有效的.
Genetic algorithm has strong global search ability, but easy to fall into local optimum. In this paper,the simulated annealing algorithm thinking is incorporated into the genetic algorithm, and the annealing processjoins the selection, crossover and mutation. The improved algorithm is used to solve the itinerary planning problem.The experimental results show that the algorithm is effective.
出处
《石家庄学院学报》
2017年第6期40-44,共5页
Journal of Shijiazhuang University
基金
2014年度安徽省质量工程项目
计算机多媒体教学团队项目(2014jxtd076)
关键词
遗传算法
模拟退火算法
行程规划
genetic algorithm
simulated annealing algorithm
itinerary planning
