The adaptive operator selection method is used to solve the global optimization problem and multi-objective optimization problem of differential evolution algorithm.However

it is difficult to find a way to properly allocate credit for the adaptive operator selection in solving the constrained optimization problem.In order to realize the adaptive strategy selection in differential evolution

we present a combined population based adaptive fitness method to achieve the credit assignment of mutate strategies for constrained optimization problems and use probability matching method to select the mutate strategy adaptively.And we also set the mutation scaling factor and the crossover rate adaptively to improve

the success rate of the algorithm.Experimental results show that the algorithm has higher accuracy and convergence speed comparing to CODEA/OED

ATMES

BBO-dm

COMDE and

DE.We also test and verify the effectiveness of the adaptive method.The algorithm can be used in forecasting

quality control

accounting process

and other scientific and engineering applications.