| 基于Pareto最优解集的多目标粒子群优化算法 |
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| 引用本文： | 裴胜玉,周永权.基于Pareto最优解集的多目标粒子群优化算法[J].计算机工程与科学,2010,32(11):85-88. |
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| 作者姓名： | 裴胜玉 周永权 |
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| 作者单位： | 广西民族大学数学与计算机科学学院,广西,南宁,530006 |
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| 基金项目： | 国家自然科学基金资助项目，广西自然科学基金资助项目，国家民委科研基金资助项目，广西民族大学科研项目启动基金资助项目 |
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| 摘 要： | 本文结合Pareto支配思想、精英保留策略、锦标赛和排挤距离选择技术,对传统的粒子更新策略进行改进,给出了一种新的粒子淘汰准则,提出了一种基于Pareto最优解集的多目标粒子群优化算法。最后,通过7个多目标标准测试函数进行测试。测试结果表明,该方法有效可行,其性能优于如NSGAII、SPEA2等多目标优化算法。
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| 关 键 词： | Pareto支配集 精英保留策略 锦标赛 排挤距离 粒子群优化算法 |
| 收稿时间： | 2009-06-12 |
| 修稿时间： | 2009-09-28 |
A Multi-Objective Particle Swarm Algorithm Based on the Pareto Optimization Solution Set |
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| PEI Sheng-yu,ZHOU Yong-quan.A Multi-Objective Particle Swarm Algorithm Based on the Pareto Optimization Solution Set[J].Computer Engineering & Science,2010,32(11):85-88. |
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| Authors: | PEI Sheng-yu ZHOU Yong-quan |
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| Affiliation: | (School of Mathematics and Computer Science,Guangxi University for Nationalities,Nanning 530006,China) |
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| Abstract: | This paper presents a novel effective multi objective particle swarm algorithm based on the Pareto non dominated set,in which the Pareto non dominated ranking,the elitism strategy,the tournament selection and the crowding distance method are integrated into a new rule by improving the update strategy of particles. Finally,seven classical functions are used to test the performance of the algorithm. Experimental results show that the proposed approach is efficient and outperforms the conventional algorithms such as NSGAII,SPEA2. |
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| Keywords: | Pareto non dominated set elitism strategy tournament selection crowding distance particle swarm optimization algorithm |
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