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An improved artificial fish swarm optimization algorithm
WU Changyou
School of Management Science and Engineering, Shandong Institute of Business And Technology, Yantai 264005, China
Abstract:In this paper, the basic principles of artificial fish's behaviors of prey, swarm, follow and bulletin board set were analyzed. Investigations were conducted to explore the reasons why it is difficult to produce the initial artificial fish swarm, and why it always falls into local optional solution. The proposed solution improves the artificial fish algorithm with the method of the produce of initial artificial fish swarm, in the artificial fish's behaviors of prey, swarm and follow introduced the adaptive mobile step length with mutation strategy into the artificial fish at the same time, avoiding fish caught in local optima, improving the ability of global optimization. Finally, through the experiment of the 4 test functions concluded that as for the function of f1, f2 and f4, while the improved artificial fish swarm algorithm and artificial fish swarm algorithm have reached the optimal value, but the convergence of the improved artificial fish swarm algorithm is faster. As to the function of f3, the standard artificial fish swarm algorithm run in to the optimal solution in several times' operation and the global optimal solution cannot be found. Therefore, the experiment shows the effectiveness and accuracy of the improved algorithm.
Key words: artificial fish swarm optimization algorithm     prey     swarm     follow     moving step length     mutation strategy

1 人工鱼群算法的基本原理

X=(x1,x2,…,xn)为人工鱼群个体向量，其中n为各条鱼寻优的变量个数，即待优化问题的变量个数，F=f(X)为某条鱼当前位置的食物浓度，其中F为目标函数，Dij=‖XiXj‖表示第i条鱼和第j条鱼之间的距离，r表示人工鱼的感知距离，人工鱼只能在其感知距离内发生觅食行为，λ为人工鱼移动的步长，δ表示拥挤度因子。其人工鱼群算法的基本原理如下。

1)觅食行为。

2)群聚行为。

3)追尾行为。

4)公告板设置。

2 改进人工鱼群算法 2.1 初始人工鱼群的产生

2.2 觅食行为的改进

2.3 群聚行为的改进

2.4 追尾行为的改进

2.5 变异策略的引入

3 仿真实验

 图 1 测试函数 f1~ f4的三维立体图 Fig. 1 The three-dimensional map test function f1~ f4

 图 2 函数 f1的迭代曲线 Fig. 2 The iterative curve of function f1

 图 3 函数 f2的迭代曲线 Fig. 3 The iterative curve of function f2

 图 4 函数 f3的迭代曲线 Fig. 4 The iterative curve of function f3

 图 5 函数 f4的迭代曲线 Fig. 5 The iterative curve of function f4

 函数 标准人工鱼群算法 改进人工鱼群算法 最优值 迭代次数 最优值 迭代次数 f1 0 14 0 8 f2 0 21 0 10 f3 2 748.8 50 3 600 6 f4 0 27 0 13

4 结束语

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DOI:10.3969/j.issn.1673-4785.201404010

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#### 文章信息

WU Changyou

An improved artificial fish swarm optimization algorithm

CAAI Transactions on Intelligent Systems, 2015, 10(03): 465-469.
DOI:10.3969/j.issn.1673-4785.201404010