| 解多目标优化问题的新粒子群存档算法 |
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| 引用本文： | 刘淳安,何广平,雍龙泉.解多目标优化问题的新粒子群存档算法[J].陕西理工学院学报(自然科学版),2005,21(3):84-86,89. |
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| 作者姓名： | 刘淳安 何广平 雍龙泉 |
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| 作者单位： | 1. 宝鸡文理学院,数学系,陕西,宝鸡,721007
2. 陕西理工学院,数学与计算机科学系,陕西,汉中,723001 |
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| 基金项目： | 宝鸡文理学院院级科研计划项目(JK2439) |
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| 摘 要： | 通过把Pareto优与粒子群优化(PSO)算法相结合,利用给出的粒子的序值定义对粒子群中的粒子进行分离存档,给出了一种求解多目标优化问题的新粒子群存档算法。为了提高算法的全局收敛性,对PSO算法中的惯性因子ω执行自适应调节。数据实验比较表明该算法能找到问题数量更多、分布更广、更均匀的Pareto最优解。
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| 关 键 词： | 多目标优化 粒子群 Pareto最优解 存档算法 |
| 文章编号： | 1002-3410（2005）03-0084-03 |
| 收稿时间： | 2005-04-04 |
| 修稿时间： | 2005-04-04 |
A new particle swarm archive algorithm for multi-objective optimization |
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| LIU Chun-an,HE Guang-ping,YONG Long-quan.A new particle swarm archive algorithm for multi-objective optimization[J].Journal of Shananxi University of Technology:Natural Science Edition,2005,21(3):84-86,89. |
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| Authors: | LIU Chun-an HE Guang-ping YONG Long-quan |
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| Abstract: | By the combination of pareto optimization and particle swarm optimization(PSO) algorithm,a new particle swarm achieve algorithm for multi-objective optimization is proposed,in which the particles are put into an achieve according to the definition of the rank of the particle.In ordering to improve its global convergence,the inertia weight of PSO algorithm has adjusted automatically.The numerical experiment shows that this algorithm can find more and wider Pareto-optimal solutions than the original one. |
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| Keywords: | multi-objective optimization particle swarm pareto optimal solution archive algorithm |
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