| 一种提高多目标进化算法搜索鲁棒最优解效率的方法 |
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| 引用本文： | 蔡自兴,朱云飞,罗彪,郑金华.一种提高多目标进化算法搜索鲁棒最优解效率的方法[J].中南大学学报(自然科学版),2011,42(4). |
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| 作者姓名： | 蔡自兴 朱云飞 罗彪 郑金华 |
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| 作者单位： | 1. 中南大学信息科学与工程学院,湖南长沙,410083
2. 湘潭大学信息工程学院,湖南湘潭,411105 |
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| 基金项目： | 国家自然科学基金，湖南省自然科学基金 |
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| 摘 要： | 提出将拉丁超立方体抽样用于计算有效目标函数,有效地提高多目标进化算法求解鲁棒最优解的效果;同时提出一种自适应抽样技术,使求解效果和效率都得到了较大的提高.通过与已有方法的对比实验,研究结果表明;本文所提出的方法求解效果好,效率较高.
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| 关 键 词： | 多目标进化算法 鲁棒最优解 有效目标函数 效率 自适应抽样 |
A method for improving performance of multi-objective evolutionary algorithms in searching robust optimal solutions |
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| CAI Zi-xing,ZHU Yun-fei,LUO Biao,ZHENG Jin-hua.A method for improving performance of multi-objective evolutionary algorithms in searching robust optimal solutions[J].Journal of Central South University:Science and Technology,2011,42(4). |
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| Authors: | CAI Zi-xing ZHU Yun-fei LUO Biao ZHENG Jin-hua |
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| Institution: | CAI Zi-xing1,ZHU Yun-fei1,LUO Biao2,ZHENG Jin-hua2 (1.School of Information Science and Engineering,Central South University,Changsha 410083,China,2.Institute of Information Engineering,Xiangtan University,Xiangtan 411105,China) |
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| Abstract: | The performance of robust optimal solutions by using Latin hypercube sampling(LHS) to compute effective objective functions was improved.Furthermore,an adaptive sampling technique was proposed,which can improve the performance and efficiency of multi-objective evolutionary algorithms(MOEAS) at a great level.Through some comparative experiments,the results demonstrate that the methods suggested in this paper are better than the existing approaches both in the performance of robust optimal solutions and the e... |
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| Keywords: | MOEAs robust optimal solutions effective objective function efficiency adaptive sampling |
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