人工鱼群算法的非线性约束优化

Nonlinear constrained optimization problems based on artificial fish-swarm algorithm

人工鱼群算法(AFSA)是一种新型的寻优策略,它具有鲁棒性强,全局收敛性好,以及对初值的不敏感性等优点。本文引入了半可行域的概念,并结合人工鱼群算法本身的特点,设计了基于竞争选择和惩罚函数的适应度函数,从而得到了一个利用AFSA算法求解约束优化问题的新进化算法。数值计算证明了算法的有效性。

Artificial Fish-Swarm Algorithm(AFSA) is a novel optimizing method.It has a strong robustness and good global astringency,and it is also proved to be insensitive to initial values.In this paper,we introduced the concept of semi-feasible region.Making use of characteristics of artificial fish-swarm algorithm,we designed the fitness function of evolutionary algorithm,which is based on tournament selection and penalty function.Then a new method is proposed,which means using the AFSA to solve constrained optimization problems.Numerical experiments demonstrate the effect of the method.