| 粒子群优化算法的分析与改进 |
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| 引用本文： | 张丽平,俞欢军,陈德钊,胡上序.粒子群优化算法的分析与改进[J].信息与控制,2004,33(5):513-517. |
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| 作者姓名： | 张丽平 俞欢军 陈德钊 胡上序 |
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| 作者单位： | 浙江大学智能信息工程研究所,浙江,杭州,310027 |
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| 基金项目： | 国家自然科学基金资助项目 ( 2 0 0 760 41) |
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| 摘 要： | 分析了惯性权值对粒子群优化(PSO)算法优化性能的影响，进而提出选择惯性权值的新策略．在随机选取惯性权值的同时，自适应地调整随机惯性权值的数学期望，有效地调整算法的全局与局部搜索能力．测试表明基于随机惯性权(RIW)策略的PSO算法，其全局搜优的速率与精度有明显提高．
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| 关 键 词： | 粒子群 优化算法 随机 惯性权 策略 |
| 文章编号： | 1002-0411(2004)05-0513-05 |
Analysis and Improvement of Particle Swarm Optimization Algorithm |
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| ZHANG Li-ping,YU Huan-jun,CHEN De-zhao,HU Shang-xu.Analysis and Improvement of Particle Swarm Optimization Algorithm[J].Information and Control,2004,33(5):513-517. |
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| Authors: | ZHANG Li-ping YU Huan-jun CHEN De-zhao HU Shang-xu |
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| Abstract: | The effects of inertia weight on particle swarm optimization (PSO) performance are analyzed. A novel method of selecting inertia weight in PSO is developed, which can tune the expectations of inertia weights adaptively when the inertia weights are randomly selected and lead to effectively balance between the local and global search ability. Results of the two benchmark functions indicate that the PSO algorithm based on the strategy of random inertia weight (RIW) has been significantly improved on both optimization speed and computational accuracy. |
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| Keywords: | particle swarm optimization algorithm random inertia weight strategy |
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