摘要
在传统人工鱼群算法的基础上,提出了一种加权平均距离人工鱼群算法(WAD-AFSA)。该算法对人工鱼群觅食行为的视野进行改进,引入一种加权平均距离策略,有效地提高了算法的收敛速度。数值仿真结果表明,与传统的人工鱼群算法相比,WAD-AFSA在标准函数测试和旅行商问题(TSP)中的优化效果更好,收敛速度更快。
Based on the traditional artificial fish swarm algorithm（ AFSA）,a weighted average distance artificial fish swarm algorithm（ WAD-AFSA） was proposed. Foraging behavior vision of the artificial fish was improved and a strategy of weighted average distance vision was introduced in WAD-AFSA. So,the convergence speed of the presented algorithm was improved. Numerical simulation results showed that compared with the traditional artificial fish swarm algorithm,the proposed WAD-AFSA converges faster and also has better optimization preference in the optimization for standard function and traveling salesman problem（ TSP）.
出处
《蚌埠学院学报》
2016年第2期15-18,共4页
Journal of Bengbu University
基金
国家自然科学基金项目(61304127)
安徽省自然科学基金项目(1408085QF132)
安徽工程大学人才引进基金项目(2013YQQ001)
关键词
旅行商问题(TSP)
人工鱼群算法
加权平均距离
路径优化
traveling salesman problem
artificial fish swarm algorithm
weighted average distance
path optimization
