摘要
蝙蝠算法作为一种新型的元启发式算法,具有优越的寻优能力和广泛的应用空间,同时也存在着收敛速度和精度的制约问题及个体之间欠缺交互等问题,针对这些不足,引入了RNA遗传算法增强个体之间的交流,通过信息的交叉和变异等变化措施,加快了算法的搜索能力,提高了搜索精度.通过测试函数验证了改进后的算法具有较好的收敛精度、可靠性和稳定性,大大提升了蝙蝠算法的寻优能力.
As a new metaheuristic algorithm,the bat algorithm has excellent search capability and can be applied to a variety of scenarios. However,the bat algorithm has problems with regard to its convergence rate and precision and the lack of interaction between individuals. In response to these deficiencies,the RNA genetic algorithm was introduced to enhance the interaction between individuals. Through the change of information,such as crossover and mutation,the search speed and precision of the algorithm can be improved. The test functions proved that the improved algorithm has good robustness,reliability and stability,which considerably improve the search capability of the bat algorithm.
作者
耿艳香
张立毅
孙云山
费腾
蒋师贤
马嘉骏
Geng Yanxiang;Zhang Liyi;Sun Yunshan;Fei Teng;Jiang Shixian;Ma Jiajun(School of Electrical and Information Engineering,Tianjin University,Tianjin 300072,China;School of Information Engineering,Tianjin University of Commerce,Tianjin 300134,China)
出处
《天津大学学报（自然科学与工程技术版）》
EI
CSCD
北大核心
2019年第3期315-320,共6页
Journal of Tianjin University：Science and Technology
基金
国家自然科学基金资助项目(61401307)
国家软科学研究计划资助项目(2014GXS4D089)
天津市应用基础与前沿技术研究计划资助重点项目(14JCZDJC32600)
天津市高等学校科技发展基金计划资助项目(20110709)
天津市应用基础与前沿技术研究计划资助项目(15JCYBJC17100)
中国物流学会资助项目(2014CSLKT3-16)
天津企业科技特派员计划项目(18JCTPJC66900)~~
关键词
蝙蝠算法
RNA遗传
交叉
变异
bat algorithm
RNA inheritance
crossover
variation
