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A Novel Elite Information Interaction Based Differential Evolution

Meta-heuristic algorithms (MHAs) have emerged in recent years to handle optimization difficulties. Due to the limitations of these algorithms, the improvement of MHAs has become a research hotspot. As one of the most representative and powerful MHA, differential evolution (DE) has become our improvement object. In this study, we improved the parent individual selection mechanism in DE mutation operation and proposed a novel elite information interaction-based differential evolution (EDE). According to the experimental results of IEEE CEC2017 benchmark functions, EDE demonstrates its superior performance.