Population-Based Algorithm with Selectable Evolutionary Operators for Nonlinear Modeling

In this paper a new population-based algorithm for nonlinear modeling is proposed. Its advantage is the automatic selection of evolutionary operators and their parameters for individuals in population. In this approach evolutionary operators are selected from a large set of operators, however only the solutions that use low number of operators are promoted in population. Moreover, assigned operators can be changed during evolution of population. Such approach: (a) eliminates the need for determining detailed mechanism of the population-based algorithm, and (b) reduces the complexity of the algorithm. For the simulations typical nonlinear modeling benchmarks are used.