| 一种新的求解多目标优化问题的遗传算法 |
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| 引用本文： | 梅羚,李元香,郑波尽.一种新的求解多目标优化问题的遗传算法[J].计算机工程与应用,2005,41(30):40-42. |
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| 作者姓名： | 梅羚 李元香 郑波尽 |
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| 作者单位： | [1]武汉大学计算机学院,武汉430072 [2]武汉大学软件工程国家重点实验室,武汉430072 |
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| 基金项目： | 国家自然科学基金（编号：60473014）;国家博士学科点科研基金（编号：20030486049） |
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| 摘 要： | 提出一种新的求解多目标优化问题的算法-GGGA。该算法运用几何斜率Pareto选择的精英策略,多个子种群从求解目标的不同方向进行区域演化,并借鉴了郭涛算法的多父体杂交算子。数据实验表明这是一种可行的有效算法。算法避免了基于Pareto占优比较的复杂性,在解空间的多样性和快速收敛性方面也显示出优越性。
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| 关 键 词： | 多目标优化 精英空间 郭涛算法 多种群 |
| 文章编号： | 1002-8331-（2005）30-0040-03 |
| 收稿时间： | 2005-06 |
| 修稿时间： | 2005-06 |
A New Genetic Algorithm in Multi-objective Optimization Problem Solving |
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| Mei Ling, Li Yuanxiang, Zheng Bojin.A New Genetic Algorithm in Multi-objective Optimization Problem Solving[J].Computer Engineering and Applications,2005,41(30):40-42. |
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| Authors: | Mei Ling Li Yuanxiang Zheng Bojin |
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| Affiliation: | Department of Computer,Wuhan University,Wuhan 430072; State Key Lab. of Software Engineering,Wuhan University,Wuhan 430072 |
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| Abstract: | GGGA is a new kind of algorithm for multi-objective optimization problem.This algorithm uses elite strategy based on geometry pareto selection(briefly called GPS);multiple subpopulations evolve from different aspects of the objectives;in every subpopulation,use multi-father crossover operator in GTA.The numerical experiments show that GGGA is feasible and effective.It avoids the complexity of non-dominated set of solutions based on Pareto front.It also provides superiority in terms of diversity and convergence.. |
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| Keywords: | multi-objective optimization elite space GTA multiple subpopulation |
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