Indexed by:会议论文
Date of Publication:2008-01-01
Included Journals:CPCI-S
Page Number:334-+
Key Words:global optimization; meta heuristics; evolutionary algorithm; real-coded; low dimensional reproduction strategy
Abstract: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.
Professor
Supervisor of Doctorate Candidates
Supervisor of Master's Candidates
Gender:Male
Alma Mater:吉林大学
Degree:Doctoral Degree
School/Department:数学科学学院
Discipline:Computational Mathematics. Financial Mathematics and Actuarial Science
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