Distributed differential evolution algorithm with adaptive parameters

An adaptive distributed differential evolution algorithm is proposed based on the change of the individual's fitness value. Firstly, the initial population is divided into several subpopulations. When the migration condition is satisfied, the best individual in each subpopulation will replace the worst individual of its neighbor subpopulations according to the Von Neumann topology. The migration mechanism among subpopulations enables the information to be communicated in the whole population. Meanwhile, the adaptive mechanism of F and CR is presented for assigning different F and CR to each individual according to the individual's fitness. Numerical results show that, the proposed algorithm is beneficial to explore the solution space, which can avoid the premature convergence and search the excellent solutions.