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| 基于动态聚集距离的多目标粒子群优化算法及其应 | |
| 引用本文： | 刘丽琴,张学良,谢黎明,李明磊,温淑花,卢青波.基于动态聚集距离的多目标粒子群优化算法及其应[J].农业机械学报,2010,41(3):189-194. |
| 作者姓名： | 刘丽琴 张学良 谢黎明 李明磊 温淑花 卢青波 |
| 作者单位： | 1. 兰州理工大学机电工程学院,兰州,730050;太原科技大学机电工程学院,太原,030024 2. 太原科技大学机电工程学院,太原,030024 3. 兰州理工大学机电工程学院,兰州,730050 |
| 基金项目： | 国家自然科学基金资助项目，山西省自然科学基金资助项目，山西高校科技研究开发项目，山西省研究生教育改革研究项目 |
| 摘 要： | 为了增加Pareto集的多样性,提高多目标优化的全局寻优能力,提出了一种基于动态聚集距离的多目标粒子群算法(DCD-MOPSO).该算法利用改进的快速排序方法来减少计算量,采用动态变化的惯性权重和加速因子以增强算法的全局寻优能力,并基于动态聚集距离对外部集进行维护以增加Pareto集的多样性.通过典型测试函数的仿真实验和应用实例对DCD-MOPSO算法性能进行了分析,并与多目标优化算法MOPSO和NSGA-Ⅱ进行了比较.结果表明,DCD-MOPSO算法收敛速度较快,且得到的Pareto集分布均匀. |
| 关 键 词： | 粒子群算法 多目标优化 改进的快速排序法 动态聚集距离 Pareto集 |
-objective Particle Swarm Optimization Algorithm Based on Dynamic Crowding Distance and Its Application |
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| Liu Liqin,Zhang Xueliang,Xie Liming,Li Minglei,Wen Shuhua,Lu Qingbo.-objective Particle Swarm Optimization Algorithm Based on Dynamic Crowding Distance and Its Application[J].Transactions of the Chinese Society of Agricultural Machinery,2010,41(3):189-194. | |
| Authors: | Liu Liqin Zhang Xueliang Xie Liming Li Minglei Wen Shuhua Lu Qingbo |
| Institution: | 1.College of Mechanical Electronic Engineering/a>;Lanzhou University of Technology/a>;Lanzhou 730050/a>;China2.College of Mechanical Electronic Engineering/a>;Taiyuan University of Science and Technology/a>;Taiyuan 030024/a>;China |
| Abstract: | A multi-objective particle swarm optimization algorithm based on dynamic crowding distance(DCD-MOPSO) was proposed.Applying the improved quick sorting to reduce the time for computation,both the dynamic inertia weight and acceleration coefficients were used in the algorithm to explore the search space more efficiently.A new diversity strategy called dynamic crowding distance was used to ensure sufficient diversity amongst the solutions of the non-dominated fronts.Some benchmark functions and the optimizatio... |
| Keywords: | Particle swarm algorithm Multi-objective optimization Improved quick sorting Dynamic crowding distance Pareto set |
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