An Improved DE Algorithm Based on the New Crossover Strategy

Abstract

Differential Evolution Algorithm (DE) is fast and stable, but it’s easy to fall into the local optimal solution and the population diversity reduces fast in the later period. In order to improve the algorithm optimization and convergence capability, this paper proposes an improved DE algorithm based on the new crossover strategy (CMDE). As to the Crossover-factor is decided by the proportion of the variance and the evolution process in each generation, so it can follow the process of evolution and constantly change; the added operation of Second Mutation can improve the capacity of solving problem, which algorithm falls into the local solution easily. With four standard test functions, the results show that the CMDE algorithm is superior to DE in convergence speed, precise and stability of algorithm.