[1]周欢,李煜.具有动态惯性权重的布谷鸟搜索算法[J].智能系统学报编辑部,2015,10(4):645-651.[doi:10.3969/j.issn.1673-4785.201409042]
 ZHOU Huan,LI Yu.Cuckoo search algorithm with dynamic inertia weight[J].CAAI Transactions on Intelligent Systems,2015,10(4):645-651.[doi:10.3969/j.issn.1673-4785.201409042]
点击复制

具有动态惯性权重的布谷鸟搜索算法

参考文献/References:
[1] YANG Xinshe, DEB S. Cuckoo search via Lévy flights[C]//World Congress on Nature & Biologically Inspired Computing. Coimbatore, India, 2009: 210-214.
[2] 李煜, 马良. 新型元启发式布谷鸟搜索算法[J]. 系统工程, 2012, 30(8): 64-69. LI Yu, MA Liang. A new metaheuristic cuckoo search algorithm[J]. Systems Engineering, 2012, 30(8): 64-69.
[3] 陈乐, 龙文. 求解工程结构优化问题的改进布谷鸟搜索算法[J]. 计算机应用研究, 2014, 31(3): 679-683. CHEN Le, LONG Wen. Modified cuckoo search algorithm for solving engineering structural optimization problem[J]. Application Research of Computers, 2014, 31(3): 679-683.
[4] OUAARAB A, AHIOD B, YANG Xinshe. Discrete cuckoo search algorithm for the travelling salesman problem[J]. Neural Computing and Applications, 2014, 24(7/8): 1659-1669.
[5] SETHI R, PANDA S, SAHOO B P. Cuckoo search algorithm based optimal tuning of PID structured TCSC controller[M]//JAIN L C, BEHERA H S, MANDAL J K, et al. Computational Intelligence in Data Mining-Volume 1. Odisha: Springer, 2015: 251-263.
[6] WALTON S, HASSAN O, MORGAN K, et al. Modified cuckoo search: a new gradient free optimisation algorithm[J]. Chaos, Solitons and Fractals, 2011, 44(9): 710-718.
[7] ZHENG Hongqing, ZHOU Yongquan. A novel cuckoo search optimization algorithm based on Gauss distribution[J]. Journal of Computational Information Systems, 2012, 8(10): 4193-4200.
[8] 苏芙华, 刘云连, 伍铁斌. 求解无约束优化问题的改进布谷鸟搜索算法[J]. 计算机工程, 2014, 40(5): 224-227, 233. SU Fuhua, LIU Yunlian, WU Tiebin. Modified cuckoo search algorithm for solving unconstrained optimization problem[J]. Computer Engineering, 2014, 40(5): 224-227, 233.
[9] 龙文, 陈乐. 求解约束化工优化问题的混合布谷鸟搜索算法[J]. 计算机应用, 2014, 34(2): 523-527. LONG Wen, CHEN Le. Hybrid cuckoo search algorithm for solving constrained chemical engineering optimization problems[J]. Journal of Computer Applications, 2014, 34(2): 523-527.
[10] VISWANATHAN G M, AFANASYEV V, BULDYREV S V, et al. Lévy flights in random searches[J]. Physica A:Statistical Mechanics and its Applications, 2000, 282(1/2): 1-12.
[11] 邓鑫洋, 邓勇, 章雅娟, 等. 一种信度马尔科夫模型及应用[J]. 自动化学报, 2012, 38(4): 666-672. DENG Xinyang, DENG Yong, ZHANG Yajuan, et al. A belief Markov model and its application[J]. Acta Automatica Sinica, 2012, 38(4): 666-672.
[12] SHI Yuhui, EBERHART R. A modified particle swarm optimizer[C]//IEEE World Congress on Computational Intelligence, The 1998 IEEE International Conference on Evolutionary Computation Proceedings. Anchorage, USA, 1998: 69-73.
[13] SHI Yuhui, EBERHART R C. Empirical study of particle swarm optimization[C]//Proceedings of the 1999 Congress on Evolutionary Computation. Washington DC, USA, 1999, 3: 1945-1949.
[14] PERAM T, VEERAMACHANENI K, MOHAN C K. Fitness-distance-ratio based particle swarmoptimization[C]//Proceedings of the 2003 IEEE Swarm Intelligence Symposium. Indianapolis, USA, 2003: 174-181.
[15] SHI Yuhui, EBERHART R C. Fuzzy adaptive particle swarm optimization[C]//Proceedings of the 2001 Congress on Evolutionary Computation. Seoul, Korea, 2001: 101-106.
[16] EBERHART R C, SHI Yuhui. Tracking and optimizing dynamic systems with particle swarms[C]//Proceedings of the 2001 Congress on Evolutionary Computation. Seoul, Korea, 2001: 94-100.
[17] ZHANG Liping, YU Huanjun, HU Shangxu. A new approach to improve particle swarm Optimization[C]//Genetic and Evolutionary Computation—GECCO 2003. Berlin Heidelberg, Germany, 2003: 134-139.
[18] 王俊伟, 汪定伟. 粒子群算法中惯性权重的实验与分析[J]. 系统工程学报, 2005, 20(2): 194-198. WANG Junwei, WANG Dingwei. Experiments and analysis on inertia weight in particle swarm optimization[J]. Journal of Systems Engineering, 2005, 20(2): 194-198.
[19] 张永韡, 汪镭, 吴启迪. 动态适应布谷鸟搜索算法[J]. 控制与决策, 2014, 29(4): 617-622. ZHANG Yongwei, WANG Lei, WU Qidi. Dynamic adaptation cuckoo search algorithm[J]. Control and Decision, 2014, 29(4): 617-622.
[20] 王凡, 贺兴时, 王燕, 等. 基于 CS 算法的Markov 模型及收敛性分析[J]. 计算机工程, 2012, 38(11): 180-182, 185. WANG Fan, HE Xingshi, WANG Yan, et al. Markov model and convergence analysis based on cuckoo search algorithm[J]. Computer Engineering, 2012, 38(11): 180-182, 185.
[21] 李枝勇, 马良, 张惠珍. 蝙蝠算法收敛性分析[J]. 数学的实践与认识, 2013, 43(12): 182-190. LI Zhiyong, MA Liang, ZHANG Huizhen. Convergence analysis of bat algorithm[J]. Mathematics in Practice and Theory, 2013, 43(12): 182-190.
[22] 刘洪波, 王秀坤, 谭国真. 粒子群优化算法的收敛性分析及其混沌改进算法[J]. 控制与决策, 2006, 21(6): 636-640. LIU Hongbo, WANG Xiukun, TAN Guozhen. Convergence analysis of particle swarm optimization and its improved algorithm based on chaos[J]. Control and Decision, 2006, 21(6): 636-640.
[23] EBERHART R C, SHI Y. Comparing inertia weights and constriction factors in particle swarm optimization[C]//Proceedings of the 2000 Congress on Evolutionary Computation. La Jolla, Germany, 2000: 84-88.
[24] 马良. 基于蚂蚁算法的函数优化[J]. 控制与决 策, 2002, 17(增刊): 719-722. MA Liang. Ant algorithm based function optimization[J]. Control and Decision, 2002, 17(S): 719-722.
[25] 李枝勇, 马良, 张惠珍. 多目标 0-1 规划问题的蝙蝠算法[J]. 智能系统学报, 2014, 9(6): 672 -676. LI Zhiyong, MA Liang, ZHANG Huizhen. Bat algorithm for the multi-objective 0-1 programming problem[J]. CAAI Transactions on Intelligent Systems, 2014, 9(6): 672-676.
相似文献/References:
[1]陈明杰,黄佰川,张旻.混合改进蚁群算法的函数优化[J].智能系统学报编辑部,2012,7(4):370.
 CHEN Mingjie,HUANG Baichuan,ZHANG Min.Function optimization based on an improved hybrid ACO[J].CAAI Transactions on Intelligent Systems,2012,7():370.
[2]刘长平,叶春明.具有Lévy飞行特征的蝙蝠算法[J].智能系统学报编辑部,2013,8(3):240.
 LIU Changping,YE Chunming.Bat algorithm with the characteristics of Lévy flights[J].CAAI Transactions on Intelligent Systems,2013,8():240.
[3]莫愿斌,马彦追,郑巧燕,等.单纯形法的改进萤火虫算法及其在非线性方程组求解中的应用[J].智能系统学报编辑部,2014,9(6):747.[doi:10.3969/j.issn.1673-4785.201309075]
 MO Yuanbin,MA Yanzhui,ZHENG Qiaoyan,et al.Improved firefly algorithm based on simplex method and its application in solving non-linear equation groups[J].CAAI Transactions on Intelligent Systems,2014,9():747.[doi:10.3969/j.issn.1673-4785.201309075]
[4]陈杰,沈艳霞,陆欣.基于信息反馈和改进适应度评价的人工蜂群算法[J].智能系统学报编辑部,2016,11(2):172.[doi:10.11992/tis.201506024]
 CHEN Jie,SHEN Yanxia,LU Xin.Artificial bee colony algorithm based on information feedback and an improved fitness value evaluation[J].CAAI Transactions on Intelligent Systems,2016,11():172.[doi:10.11992/tis.201506024]
[5]吴一全,周建伟.布谷鸟搜索算法研究及其应用进展[J].智能系统学报编辑部,2020,15(3):435.[doi:10.11992/tis.201811005]
 WU Yiquan,ZHOU Jianwei.Overview of the cuckoo search algorithm and its applications[J].CAAI Transactions on Intelligent Systems,2020,15():435.[doi:10.11992/tis.201811005]

备注/Memo

收稿日期:2014-09-30;改回日期:。
基金项目:河南省科技攻关重点基金资助项目(122102210201);河南大学研究生教育综合改革基金资助项目(Y1427056).
作者简介:周欢,1990年生,女,硕士研究生,主要研究方向为智能优化、电子商务;李煜,1969年生,女,教授,博士,主要研究方向为智能优化、电子商务、物流管理。
通讯作者:李煜.E-mail:lyhenu@163.com.

更新日期/Last Update: 2015-08-28
Copyright © 《 智能系统学报》 编辑部
地址:(150001)黑龙江省哈尔滨市南岗区南通大街145-1号楼 电话:0451- 82534001、82518134 邮箱:tis@vip.sina.com