一种随机搜索优化算法——网鱼算法

A Random Exploring Optimization Algorithm:Wang-Yu Algorithm

从随机搜索优化的最基本的特征出发,采用连动随机策略,在计算机上先编织两类(一大一小)特殊数据网.然后通过在整个搜索范围内进行有序的合理撒网,并及时观察撒网后的动态,从一新的角度较好实现了随机搜索优化的目标.在针对一些典型算法测试函数的测试实验中,通过比较网鱼算法与遗传算法,结果显示:当面对的问题事先不知道任何有关最优者的特点时,网鱼算法比遗传算法更一般化,适应的问题更宽广.

Inspired by the thought of netting fish in our daily life, Wang-Yu Algorithm starts from the most basic characteristics of the random exploring optimization and it ties up two special kinds of data-nets firstly in computer by using the tactics of random moving together. Then Wang-Yu Algorithm realizes the object of random exploring optimization from a new direction by netting orderly in the all range of exploring and promptly observing the situation after netting. From comparing Wang-Yu Algorithm with Genetic Algorithm in test experiment to the typical algorithm test functions, it is shown that the Wang-Yu Algorithm is more general and the more suitable to deal with the problem tha, Genetic Algorithm when few characteristics about the most excellent object are known before in a problcm.