摘要
传统遗传算法的收敛速度与问题解的质量是影响算法寻优性能的一对主要矛盾。文章针对上述矛盾,提出了改进遗传算法的控制策略—杂交、变异的并行处理、基于适应值密度的变异操作、自调整父代迁移策略和父代与子代竞争策略。并应用于TSP问题中,验证了算法的有效性。
The convergence speed of genetic algorithm and the quality of problem result are the main inconsistency which affects the performance of GA.The paper proposes the control strategies of improved GA,which are parallel operation of crossover and mutation, mutation based on the density of fitness, the adaptive migration of father generation and competition of father generation and filial generation. Furthermore, its efficiency is shown by an application in TSP.
出处
《计算机工程》
CAS
CSCD
北大核心
2002年第9期90-92,共3页
Computer Engineering
