Unconstrained optimization with improved differential evolution algorithm having variable dynamic non-linear increased crossover

This paper presents improved differential evolution (IDE) algorithm with variable dynamic non-linear increased crossover rate. The IDE algorithm is proposed recently with dynamic nonlinear increased crossover rate for global optimization of nonlinear functions. In variable dynamic nonlinear increased crossover rate, the parameter k is made variable in the range [1,10]. The proposed algorithm is tested for five benchmark functions, namely, Ackley, Griewank, Rastrigin, Schefel2.22 and Sphere. The results show that the IDE produced better results with variable dynamic non-linear increased crossover rate.