The Research of Self-Adaptive Differential Evolution Algorithm with Opposition-Based Mechanisms

In this paper we describe an algorithm which is based on Differential Evolution Algorithm using self-adaption and opposition-Based Mechanisms (SAODE). The mutation control parameter f i is self-adapted according to the deviation of search parameters in each generation. Opposition-based optimization is included in the initialization, and in the evolutionary process itself. In order to demonstrate the behavior of our algorithm we applied it in 4 benchmark functions with a combination of self-adaptive and opposition-based optimization. According to the obtained results, SAODE surpasses DE on 3 functions among 4 test functions about the convergence speeds.