论文修改版.doc

带认知因子的交叉鸽群算法收稿日期:2017-3-10
基金项目:四川省科技厅支撑计划项目( 2016GZ0091,2016GZ0092)
作者简介:陶国娇(1991-),女,.
通信作者:李智,E—mail:******@scu.
陶国娇,李智
(四川大学电子信息学院,四川成都 610064)
摘要:鸽群优化算法在求解最优问题时易早熟收敛,陷入局部最优,,将地图指南针算子和地标算子进行联合交叉运行;然后,在地图和指南针算子中引入了非线性递增的认知因子,并将其视为运动权值的三角函数;最后,在地标算子中,引入呈三角函数递增的压缩因子,,改进后的算法搜索成功率有很大的提高,能有效地避免早熟收敛,跳出局部极值,具有更好地寻优能力.
关键词:鸽群算法;联合;交叉;认知因子;压缩因子;统一性
中图分类号: 文献标识码: A
A Crossed Pigeon-inspired Optimization Algorithm with Congnitive Factor
TAO Guojiao,LI Zhi
(College of Electronics and Information EngineeringSichuan University,Chengdu 610064,China)
Abstract: In solving optimal problems, pigeon-inspired optimization algorithm (PIO) is easy to premature convergence and trap in local optimum, so this paper presents a cross pigeon-inspired optimization algorithm with cognitive factors. Firstly, map pass operator and landmark operator no longer run independently, and them are mixed together and operated crosswise; Second, in the map pass operator the cognitive factor of nonlinear increment was introduced, and regard as the inertia weight’s trigonometric functions; Finally, in the landmark operator, pressive factor that was increasing gradually in the form of trigonometric functions was proposed to make path smoother. Simulation results showed that the improved algorithm search ess rate had greatly improved, and not only