Dynamic differential evolution algorithm with random mutation

Abstract

The dynamic Differential Evolution(DE) algorithm with random mutation was proposed.In this algorithm,the mutation strategies of DE/rand/1 and DE/best/1 were combined by linear decreased weight convex combination strategy to produce a new mutation strategy so as to dynamically use the advantages of DE/rand/1 and DE/best/1.In order to improve the global optimization ability of DE algorithm,exponent increased crossover probability operator,linear decreasing scaling factor and random mutation mechanism were introdunced.The test results on the four standard test functions show that the new algorithm has fast convergence,high accuracy and more robustness,more suitable to solve high-dimensional complex global optimization problems.