| 一种多项指标全提升的多目标优化演化算法 |
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| 引用本文： | 宋中山,陈建国,郑波尽.一种多项指标全提升的多目标优化演化算法[J].中南民族大学学报(自然科学版),2011,30(3):89-93. |
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| 作者姓名： | 宋中山 陈建国 郑波尽 |
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| 作者单位： | 中南民族大学计算机科学学院,武汉,430074 |
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| 基金项目： | 国家自然科学基金资助项目(60803095) |
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| 摘 要： | 针对当前大部分多目标优化演化算法设计复杂、耗时巨大,以及取得的近似Pareto前沿点不够多、分布不均匀、覆盖不完整等问题,提出了一种新的基于粒子群和几何Pareto选择算法的多目标优化PSGPS算法.经过5个测试问题的实验结果表明:该算法使用较低的时间消耗,就能在前沿点个数、前沿点分布均匀性、覆盖完整度等性能指标上都优于当前流行的NSGA2,SPEA2和PESA等多目标优化演化算法.
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| 关 键 词： | 演化算法 多目标优化 粒子群优化 |
A Multi-Objective Optimization Evolutionary Algorithm with Multiple Indicators Enhanced |
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| Song Zhongshan,Chen Jianguo,Zheng Bojin.A Multi-Objective Optimization Evolutionary Algorithm with Multiple Indicators Enhanced[J].Journal of South-Central Univ for,2011,30(3):89-93. |
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| Authors: | Song Zhongshan Chen Jianguo Zheng Bojin |
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| Institution: | Song Zhongshan,Chen Jianguo,Zheng Bojin (College of Computer Science,South-Central University for Nationalities,Wuhan 430074,China) |
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| Abstract: | Currently,most of multi-objective optimization evolutionary algorithms are complex and time-consuming.At the same time,the approximate Pareto fronts of these algorithms may not have enough points,with uneven in distribution and incomplete coverage.This paper presents a new multi-objective optimization evolutionary algorithm,which is based on Particle Swarm Optimization algorithm and Geometric Pareto selection algorithm.The experimental results on five widely used test-problems show that the performance indi... |
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| Keywords: | evolutionary algorithm multi-objective optimization particle swarm optimization |
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