An uncertain optimization method based on interval differential evolution and adaptive subinterval decomposition analysis

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.