An uncertain optimization method based on interval differential evolution and adaptive subinterval decomposition analysis. (August 2019) - Fu, Chunming; Cao, Lixiong
Highlights: A new optimization method is proposed to directly solve the interval uncertain problems with interval uncertainties. Adaptive decomposition analysis is utilized to calculate intervals of functions caused by uncertainties. The accuracy and efficiency of proposed method is verified. Abstract: An interval differential evolution (IDE) with adaptive subinterval decomposition analysis is suggested to directly solve the nonlinear uncertain optimization problems with interval parameters. The adaptive subinterval decomposition analysis technique is proposed to calculate the upper and lower bounds of objective function and constraints caused by interval uncertainties. An adaptive convergence mechanism is utilized to ensure the accuracy of achieved bounds. Moreover, within the framework of IDE, the interval possibility model is employed to deal with the interval constraints of uncertain optimization problems and the interval preferential rule is used to select the promising solutions to retain into the next evolutionary population. Both numerical and engineering examples are eventually given to demonstrate the validity of the proposed method.