捕食-被食动力学优化算法

Predator-prey Dynamics-based Optimization

为了解决复杂函数优化问题,提出了捕食-被食动力学优化算法。该算法假设在某生态系统中有捕食者和被食者两个种群。两类种群内部有竞争,种群内部密度越高竞争越激烈,种群特征更容易产生变化;强壮种群更容易在竞争中战胜弱势种群,从而使得自身特征发生较大改变。捕食者种群食用被食者种群后,其特征也发生变化。根据上述特点构造出了竞争算子、捕食-被食算子和生长算子,这些算子有利于使搜索跳出局部陷阱。本算法具有全局收敛性的特点,可求解一类极复杂优化问题。

To solve the complex function optimization problem, a predator-prey dynamics optimization algorithm is proposed. The algorithm assumes that there are two species of predator and prey in an ecosystem. There is competition among the same species, the higher the population density, the more intense the competition, and then characteristics of populations are more likely to produce changes; strong populations are more likely to defeat weak populations when competition, and thus to obtain significant changes in their own characteristics. When predator populations eat prey populations, their characteristics also change. The competition operator, the predator-prey operator and the growth operator are constructed by use of the above relationship of ecosystem phenomena, these operators are helpful to make the search jump out of the local trap. The algorithm is globally convergent and can be used to solve a class of extremely complex optimization problems.