Memory-Based Differential Evolution Algorithms with Self-Adaptive Parameters for Optimization Problems

In this study, twelve modified differential evolution algorithms with memory properties and adaptive parameters were proposed to solve the optimization problem. In the experimental process, these modified differential evolution algorithms were applied to 23 continuous test functions. Experiments show that MBDE2 and IHDE-BPSO3 are superior to the original differential evolution algorithm and its extended variants, and the best solutions can be found in most of the problems. It is inducted that the proposed improved differential evolution algorithm can adapt to most problems and obtain better results, and adding the concept of memory property is a great improvement to the capability of the proposed improved differential evolution algorithm.