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| 基于Predator-Prey行为的双种群粒子群优化算法 | |
| 引用本文： | 秦全德,牛奔,李丽,李荣钧.基于Predator-Prey行为的双种群粒子群优化算法[J].信息与控制,2011,40(6):733-739. |
| 作者姓名： | 秦全德 牛奔 李丽 李荣钧 |
| 作者单位： | 1. 深圳大学管理学院,广东 深圳,518060 2. 深圳大学管理学院,广东 深圳 518060;中国科学院合肥智能机械研究所,安徽 合肥 230031 3. 华南理工大学工商管理学院,广东 广州,510640 |
| 基金项目： | 国家自然科学基金资助项目(71071057,71001072); 中国博士后基金资助项目(20100480705) |
| 摘 要： | 根据生物的捕食-食饵(predator-prey)行为的规律,提出了一种双种群粒子群优化(DPPSO)算法.将粒子分成predator和prey两个种群,其中predator种群每间隔一定的迭代次数后排斥prey种群.在排斥的过程中,predator种群采用“擒贼先擒王”的策略,逐步向prey种群的群体最优位置靠近,同... |
| 关 键 词： | 粒子群优化 predator-prey行为 双种群 基准函数 |
A Double-Population Particle Swarm Optimization Algorithm Based on Predator-Prey Behavior |
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| QIN Quande , NIU Ben , LI Li , LI Rongjun.A Double-Population Particle Swarm Optimization Algorithm Based on Predator-Prey Behavior[J].Information and Control,2011,40(6):733-739. | |
| Authors: | QIN Quande NIU Ben LI Li LI Rongjun |
| Affiliation: | QIN Quande~1,NIU Ben~(1,2),LI Li~1,LI Rongjun~3 (1.College of Management,Shenzhen University,Shenzhen 518060,China,2.Hefei Institute of Intelligent Machines,Chinese Academy of Sciences,Hefei 230031,3.School of Business Administration,South China University of Technology,Guangzhou 510640,China) |
| Abstract: | According to biological rules of predator-prey behavior,a double-population particle swarm optimization (DPPSO) algorithm is proposed.The particles are divided into two populations,the predator population and the prey population. The particles in the predator population exclude those in prey population in a certain interval of iterations.During the course of exclusion,particles in predator population adopt the strategy of catching the ringleader first in order to capture all his bandit followers,which means... |
| Keywords: | particle swarm optimization predator-prey behavior double populations benchmark function |
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