Combination of genetic algorithm and ant colony algorithm for distribution network planning

被引：0
|
作者：
Dong, Yong-Feng [1 ]
Gu, Jun-Hua [1 ]
Li, Na-Na [1 ]
Hou, Xiang-Dan [1 ]
Yan, Wei-Li [1 ]
机构：
[1] Hebei Univ Technol, Tianjin 300401, Peoples R China
来源：
PROCEEDINGS OF 2007 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-7 | 2007年
关键词：
ant colony algorithm; genetic algorithm; distribution network planning; combinatorial optimization;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Ant Colony Algorithm is one kind of new heuristic biological modelling method which has the ability of parallel processing and global searching, but its convergence speed is slow because of poor pheromone on the early path. In this paper, discuss a new algorithm which combines genetic algorithm and Ant colony algorithm. Genetic Algorithm is added to Ant Colony Algorithm's every generation in the proposed algorithm. Making use of Genetic Algorithm's advantage of whole quick convergence, Ant Colony Algorithm's convergence speed is quickened. Genetic Algorithm's mutation mechanism improves the ability of Ant Colony Algorithm to avoid being trapped in a local optimal. The simulation shows that the new algorithm is effective in solving distribution network planning problem.
引用
收藏
页码：999 / 1002
页数：4
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