Abstract: 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.

Key words: evolution algorithm, intelligent optimization algorithm, meta-heuristic search, population dynamics, predator-prey dynamics model