| 反向认知的高效果蝇优化算法 |
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| 引用本文： | 韩俊英,刘成忠.反向认知的高效果蝇优化算法[J].计算机工程,2013(11):223-225,239. |
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| 作者姓名： | 韩俊英 刘成忠 |
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| 作者单位： | 甘肃农业大学信息科学技术学院,兰州730070 |
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| 基金项目： | 国家自然科学基金资助项目（61063028）;甘肃省科技支撑计划基金资助项目（1011NKCA058）;甘肃省教育厅科研基金资助项目（1202-04）;甘肃省高等学校科研基金资助项目（2013A-060） |
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| 摘 要： | 针对果蝇优化算法的早熟收敛问题，提出一种基于最优和最差个体协同学习的果蝇优化算法。该算法通过在进化方程中添加向最差个体学习的改进策略，优化进化方程，增强算法跳出局部最优、寻找全局最优的能力。对经典测试函数的仿真结果表明，该算法具有更好的全局搜索能力，在收敛速度、收敛可靠性及收敛精度上比其他算法有较大的提高。
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| 关 键 词： | 果蝇优化 群体智能 反向认知 协同学习 优化进化方程 收敛精度 |
Efficient Fruit Fly Optimization Algorithm with Reverse Cognition |
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| HAN Jun-ying,LIU Cheng-zhong.Efficient Fruit Fly Optimization Algorithm with Reverse Cognition[J].Computer Engineering,2013(11):223-225,239. |
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| Authors: | HAN Jun-ying LIU Cheng-zhong |
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| Affiliation: | (Information Institute of Science and Technology, Gansu Agricultural University, Lanzhou 730070, China) |
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| Abstract: | Considering the premature convergence problem of Fruit fly Optimization Algorithm（FOA）, a new collaborative learning FOA based on the best and the worst individual is presented. The evolutionary equation is optimized by adding learning the worst individual to it. The ability of the algorithm to break away from the local optimum and to find the global optimum is greatly enhanced. Experimental resut~ show that the new algorithm has the advantages of better global search ability, speeder convergence and more precise convergence. |
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| Keywords: | fruit fly optimization swarm intelligence reverse cognition collaborative learning optimization evolution equation convergence precision |
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