| 基于遗传交叉因子的改进蜂群优化算法* |
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| 引用本文： | 罗钧,樊鹏程. 基于遗传交叉因子的改进蜂群优化算法*[J]. 计算机应用研究, 2009, 26(10): 3716-3717. DOI: 10.3969/j.issn.1001-3695.2009.10.033 |
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| 作者姓名： | 罗钧 樊鹏程 |
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| 作者单位： | 重庆大学,光电技术及系统教育部重点实验室,重庆,400030 |
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| 基金项目： | 国防科工委国防军工计量“十一五”计划重点资助项目（B20301118） |
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| 摘 要： | 针对标准蜂群算法在求解函数优化问题时易陷入局部极优点的缺陷，提出了一种基于遗传交叉因子的改进蜂群优化算法。该算法借鉴遗传算法中的选择交叉操作增加食物源多样性，通过引入交叉因子增强群体食物源的优良特性，减小陷入局部极值的可能。对几个典型的测试函数进行仿真表明，该算法较标准蜂群算法提高了全局搜索能力和收敛速度，改善了优化性能。
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| 关 键 词： | 蜂群算法；交叉因子；收益度；遗传算法 |
Improved particle swarm optimization based on genetic hybrid genes |
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| LUO Jun,FAN Peng-cheng. Improved particle swarm optimization based on genetic hybrid genes[J]. Application Research of Computers, 2009, 26(10): 3716-3717. DOI: 10.3969/j.issn.1001-3695.2009.10.033 |
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| Authors: | LUO Jun FAN Peng-cheng |
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| Affiliation: | (Key Laboratory of Optoelectronic Technology & System, Ministry of Education, Chongqing University, Chongqing 400030, China) |
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| Abstract: | A drawback of artificial bee colony algorithm is easily trapped in a local optimal solution.The paper presented an improved artificial bee colony algorithm based on genetic hybrid gene.The food sources were multiple by the selection and hybridization of genetic arithmetic.The import of hybrid genes improved excellent performance of particles and reduced likelihood on getting into local optimization.Experimental results show that the new algorithm can greatly improve the global convergence ability and enhance the rate of convergence. |
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| Keywords: | bee colony algorithm hybrid genes nectar amounts genetic arithmetic |
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