关键词: 早熟收敛, 密度聚类, 小生境, 差分进化, 种群多样性

Abstract: Considering the premature convergence problem in the conventional differential evolution algorithm，a density clustering based niching Differential Evolution algorithm is proposed in this paper.Based on the strong global searching ability and good robustness of DE/rand/2/bin mutation scheme and the good performance of local searching ability and fast convergence speed of DE/best/2/bin mutation scheme，the algorithm initializes a global population without sub-populations at first，then iteratively searches the global population employing DE/rand/2/bin scheme and makes clustering to individuals，a niche sub-population forms when the individual amounts in cluster reach the smallest size specified，and then iteratively searches sub-populations employing the improved DE/best/2/bin scheme and makes clustering again，so as to improve the population diversity in the process of evolution，and strengthen the ability of avoiding local optimization.Simulation result shows that the algorithm can greatly improve the convergence speed and the global searching ability，and efficiently avoid premature convergence.

Key words: premature convergence, density clustering, niching, Differential Evolution（DE）, population diversity