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论文类型：会议论文

发表时间：2008-01-01

收录刊物：CPCI-S

页面范围：334-+

关键字：global optimization; meta heuristics; evolutionary algorithm; real-coded; low dimensional reproduction strategy

摘要：The strategy of low dimensional reproduction (LDR) is proposed for real-coded evolutionary algorithms (REAs) in this paper It preserves some (randomly chosen) components of the local best vector (elite individual) in the reproduction process and let the traditional reproduction operators act on the rest components. Thus it could help the search points escape from the hyperplane where the parents individuals lies, as well as keep them from getting too much decentralized and search mainly along a series of orthogonal directions (coordinate). The LDR strategy provides a universal idea to improve the performance of REAs. Four REAs are taken as examples to show the effect of the strategy. Numerical results show that the proposed strategy can accelerate the convergence speed of the applied algorithms considerably. In addition, the strategy is computational saving, easy to implement, and easy to control.