摘要
针对标准遗传算法收敛速度慢以及易陷入局部最优的问题,采用基于工序的编码和活动解码方式,采用自适应策略设计交叉算子和变异算子,并将极值优化算法作为一种新的变异算子对标准遗传算法进行了改进,最后通过实验验证了改进后算法的有效性。
In view of the standard genetic algorithm having many problems, such as a slow convergence speed and being easily trapped in local optimal, this paper puts forward a series of improvements： encoding based on the process, decoding the active scheduling, improving self adaptive probability, introducing EO as a GA＇s variation operator. At last. the experiment verifies the improved algorithm is feasihle and it can get very satisfactory results.
出处
《机械工程师》
2014年第1期127-130,共4页
Mechanical Engineer
