| 基于多样性优化策略的粒子群算法 |
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| 引用本文： | 朱孝晶,周圆兀,龚熠,蔡雪霁,张向华. 基于多样性优化策略的粒子群算法[J]. 广西工学院学报, 2011, 22(1): 74-77 |
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| 作者姓名： | 朱孝晶 周圆兀 龚熠 蔡雪霁 张向华 |
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| 作者单位： | 1. 广西工学院,土木建筑工程系,广西,柳州,545006
2. 广西工学院,生物与化学工程系,广西,柳州,545006 |
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| 基金项目： | 国家自然科学基金，广西教育厅基金，广西工学院博士基金 |
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| 摘 要： | 针对标准粒子群优化算法(SPSO)存在粒子群多样性丢失而易陷入局部最优的问题,提出了一种改进优化算法(PSOBF),该算法通过引入排斥操作而提高了搜索效率.通过对4个标准测试函数的性能数值实验对比,并比较了PSOBF、SPSO及ARPSO算法结果,证实PSOBF可以较好地实现全局与局部搜索的平衡,表明改进算法是有效的.
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| 关 键 词： | 粒子群优化 多样性 策略 平衡 |
Particle Swarm Optimization Algorithm Based on Diversity Strategy |
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| ZHU Xiao-jing,ZHOU Yuan-wu,GONG Yi,CAI Xue-ji,ZHANG Xiang-hua. Particle Swarm Optimization Algorithm Based on Diversity Strategy[J]. Journal of Guangxi University of Technology, 2011, 22(1): 74-77 |
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| Authors: | ZHU Xiao-jing ZHOU Yuan-wu GONG Yi CAI Xue-ji ZHANG Xiang-hua |
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| Affiliation: | a (a.Department of Civil Engineering,b.Department of Biological and Chemical Engineering, Guangxi University of Technology,Liuzhou 545006,China) |
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| Abstract: | There is loss of particle swarm diversity issues related to Standard Particle Swarm Optimization,which is easily trapped into local optimum.This article proposes a solution to improve particle swarm diversity loss optimization algorithm(PSOBF).The strategy introduces exclusive operation,and enhances the search efficiency.Through PSOBF algorithm analysis of the four standard test functions and comparing with the existing SPSO algorithm and another ARPSO algorithm,we find that PSOBF algorithm can achieve a better algorithm for the balance of global and local search,and it’s effective. |
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| Keywords: | particle swarm optimization diversity strategy balance |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
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