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一种用Powell方法局部优化的人工萤火虫算法
  • ISSN号：1003-6059
  • 期刊名称：《模式识别与人工智能》
  • 时间：0
  • 分类：TP181[自动化与计算机技术—控制科学与工程;自动化与计算机技术—控制理论与控制工程]
  • 作者机构：[1]广西民族大学数学与计算机科学学院,南宁530006
  • 相关基金：国家自然科学基金（No.61165015）、广西省自然科学基金（No.0991086）资助项目
作者： 张军丽[1], 周永权[1]
关键词： Powell方法, 人工萤火虫算法(GSO), 函数优化, Powell Method, Glowworm Swarm Optimization （GSO）, Function Optimization
中文摘要：

针对人工萤火虫算法在寻找函数全局最优值时，存在着收敛速度慢、易陷入局部最优、收敛成功率和求解精度低等不足，利用Powell方法强大的局部优化能力，将其作为一局部搜索算子嵌入到人工萤火虫算法，提出一种用Powell方法局部优化的人工萤火虫算法．最后，8个标准函数测试结果表明，改进后人工萤火虫算法在收敛速度、精度和稳定性方面都优于人工萤火虫算法．

英文摘要：

In order to overcome the shortcomings of artificial glowworm swarm optimization （GSO） algorithm including slow convergence speed, easily falling into local optimum value, low computational accuracy and low success rate of convergence, an artificial GSO algorithm based on Powell local optimization method is proposed. It adopts the powerful local optimization ability of Powell method and embeds it into GSO as a local search operator. Experimental results of 8 typical functions show that the proposed algorithm is superior to GSO in convergence efficiency, computational precision and stability.

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期刊信息
  • 《模式识别与人工智能》
  • 中国科技核心期刊
  • 主管单位:中国科学技术协会 中国自动化学会
  • 主办单位:国家智能计算机研究开发中心 中国科学院合肥智能机械研究所
  • 主编：郑南宁
  • 地址：安徽省合肥市蜀山湖路350号中国科学院合肥智能机械研究所
  • 邮编：230031
  • 邮箱：bjb@iim.cas.cn
  • 电话：0551-5591176
  • 国际标准刊号：ISSN：1003-6059
  • 国内统一刊号：ISSN：34-1089/TP
  • 邮发代号:26-69
  • 获奖情况:
  • 国内外数据库收录:
  • 被引量:10169