演化式果蝇算法及其应用研究

Evolutionary Fruit Algorithm and Its Application Research

现实中的大量问题都可以转化为函数优化问题,而寻找优化问题的通用高效算法,是智能计算所要达到的主要目的之一。文中基于果蝇觅食行为的社会特性,设计了一种求解函数优化问题的演化式果蝇算法。该算法首先定义了果蝇味道浓度判定值及果蝇味道浓度判定函数,针对多维度问题,提出了距离分量及味道浓度判定值分量的概念,并将其用于引导果蝇搜索过程之中,得到了较理想的寻优结果。实验表明,算法具有较高的效率、良好的全局性能及普适性。

Large number of problems in reality may convert into function optimization problem, and the general and efficient algorithm of search for optimization problems is one of the main purposes of intelligent computing achieving. In this paper,based on the fruit foraging behavior characteristics of the group, designed a evolutionary fruit algorithm for solving function optimization problem. The algorithm f＇trstly defines the fruit smell concentration determination value and fruit smell concentration detection function, and then for the multi-di- mensional problem, puts forward the concept of distance components and smell concentration determination value component, and uses to guide the search process of fruit, getting the ideal optimization results. The numerical experiments show that the algorithm has high effi- ciency, global performance and good universality.