摘要
为了改善遗传算法在水库优化调度中的应用效果,采用自适应遗传算法和广度变异模块相结合的分层收敛算法:第一层采用广度变异和外部存档的方式改善种群的多样性;第二层嵌套广度变异模块,并采用自适应遗传算法进行全局搜索。通过比较自适应遗传算法和分层进化算法,结果显示:基于遗传算法的分层算法具有高效的全局搜索能力,避免了自适应遗传算法陷入局部最优的缺陷,在一定收敛条件下得到了更接近全局最优的目标值。
To improve the solution searching efficiency of genetic algorithm in the optimization of reservoir operation, a hierarchy evolution algorithm with a deep mutation and adaptive genetic algorithm was introduced. First hierarchy adopted deep mutation and external archive to enhance diversity of population ; and second hierarchy inserted deep mutation and adopted adaptive genetic algorithm to search global optimal solution. The results of ap- plication in reservoir operation using respectively the adaptive genetic algorithm combing deep mutation and the hierarchy algorithm were compared, which showed that the new algorithm yielded a better result. The new algorithm has efficient global searching ability, and effectively avoided sinking into local optimal and further. Finally, the research has obtained a better global optimal solution under a certain convergence criterion.
出处
《人民黄河》
CAS
北大核心
2012年第8期54-56,143,共4页
Yellow River
基金
水利部公益性行业科研专项(200801005)
关键词
水库调度
遗传算法
广度变异
分层进化
外部存档
自适应
reservoir operation
genetic algorithm
deep mutation
hierarchy evolution
external archive
self-adaptation