摘要
针对遗传算法在进行多目标优化时,收敛速度慢且易早熟的问题,提出一种改进自适应遗传算法,改进了选择方法和终止判据,并对交叉和变异概率的选取进行了自适应处理。针对含分布式发电的配电网规划的多目标性,采用模糊理论引入总体满意度很好地解决了多目标归一化问题。仿真算例表明:改进的算法能有效地寻找到全局最优解,明显提高收敛速度,具有良好的自适应特性。
The genetic algorithm has some defects for optimizing multi-objectives, such as slow convergent speed and easily premature. An improved self-adaptive genetic algorithm was proposed, for improving terminational criterion and method of selection, making a self-adaptive disposal in crossover and mutation probability. Considering multi-objectives of distribution network plan- ning including distributed generation, this article introduced totally satisfied degree by employing the fuzzy optimal theory, which was a good way to transform multi-objectives into single objective. Results of a system simulation showed that this algorithm could seek the best result of overall situation effectively, increase the convergence speed obviously, and had favorable self-adaptive characteristics.
出处
《沈阳农业大学学报》
CAS
CSCD
北大核心
2007年第4期590-593,共4页
Journal of Shenyang Agricultural University
基金
河北省科技厅资助项目(072135124)
河北省教育厅资助项目(2005328)
关键词
改进自适应遗传算法
分布式发电
多目标优化
模糊优化
配电网规划
improved self-adaptive genetic algorithm
distributed generation
multi-objective optimization
fuzzy optimization
distribution network planning