摘要
基于信息素动态更新的蚁群算法(DACO)求解大规模最短路由问题收敛时间过长,单亲进化遗传算法(PEGA)在产生初始种群、选择父体及基因换位等操作中存在随机性太大的问题,论章将这两种算法相结合,提出了基于改进蚁群算法的单亲进化遗传算法(DACO-PEGA),该算法通过控制蚁群周游次数,求得满意可行解或次优解,再将已得路由作为初始种群进行优化改良,求得最短路由。实验结果表明,该算法应用于求解最短路由问题行之有效.
Because DACO(ant colony optimization based on dynamic pheromone updating) algorithm costs too much time in order to find an optimal solution in solving the Shortest Route Problem for large-scaled optimization,and PEGA(partheno-evolution genetic algorithm) is too highly optional in producing primal group,choosing father-body,gene exchange operator,this article combines the two algorithms and puts forth the PEGA based on DACO.Through controlling covering times of ant colony,it firstly attains better solution,and secondly improves the attained solution as primal group to come at the best solution.The experiments demonstrate that the proposed algorithm is very effective in solving the Shortest Route Problem.
出处
《计算机工程与应用》
CSCD
北大核心
2005年第8期64-67,共4页
Computer Engineering and Applications
基金
国家自然科学基金资助(编号:10171095)
国家863高技术研究发展计划项目(编号:2002AA103061)
