摘要
针对传统蚁群算法容易出现早熟、收敛速度慢等问题,提出一种将鱼群与蚁群混合算法,并将其应用于配电网故障定位中。该算法利用人工鱼群算法的克服局部极值取得全局极值的能力,改善了人工蚁群算法的早熟问题。同时考虑到配电网的特殊性质,采用二进制编码规则,优化了编码方式,使得算法的全局寻优能力大大增强。
Due to such disadvantages of traditional ant colony optimization (ACO) as prematurrity, slow convergence and so on, a mixture of the fish and ant colony algorithm was proposed and applied to fault location in distribution networks. The algorithm uses artificial fish algorithm to overcome the local minimum and to obtain global minimum, improving the prematurity of the artificial ant colony algorithm. Taking into account the special nature of the distribution network, the binary encoding rules was used to optimize the encoding and the ability of global optimization of the algorithm was greatly enhanced.
出处
《黑龙江科学》
2011年第4期30-32,57,共4页
Heilongjiang Science
关键词
故障定位
蚁群算法
鱼群算法
Fault location
ant colony optimization
artifical fish swarm optimization