摘要
针对传统蚂蚁遗传混合算法收敛速度慢的特点,提出了一种新的动态蚂蚁遗传混合算法。新算法采用最佳融合点评估策略,动态地控制遗传算法与蚂蚁算法的调用时机,并设计了相应的信息素更新方法,有效减少了算法的冗余迭代次数,提高了搜索速度;同时引入迭代调整阈值控制算法后期的遗传操作和蚂蚁规模,加快了种群进化速度,从而更快地找到最优解。通过对Muth and Thompson基准问题进行计算机仿真,实验证明新算法收敛速度得到了提高。
To increase the convergence speed of the conventional ant algorithm-genetic algorithm, a new algorithm named dynamic ant algorithm-genetic algorithm was proposed. The proposed algorithm employed the best melting point evaluation strategy to control the calling of the two algorithms dynamically. In addition, the corresponding strategy to update the information cell to reduce the redundant times of iteration and increase the searching speed was also introduced in the algorithm. Yurthermore, the iteration adjustment threshold was introduced as well to not only control the genetic operation and size of the ant population in the later phase of the algorithm but also speed up the evolution process of the population so as to find the optimal solution faster. Computer simulation was carried out for Muth and Thompson standard problem, which showed that the convergence speed of the proposed algorithm was increased sharply.
出处
《计算机集成制造系统》
EI
CSCD
北大核心
2008年第8期1566-1570,共5页
Computer Integrated Manufacturing Systems
基金
大连市计划资助项目(2007A10GX110)
大连市青年科技人才基金资助项目(2006J23JH039)
辽宁省基金资助项目(20072161)~~
