[1]黎延海,雍龙泉,拓守恒.随机交叉-自学策略改进的教与学优化算法[J].智能系统学报,2021,16(2):313-322.[doi:10.11992/tis.201910045]
 LI Yanhai,YONG Longquan,TUO Shouheng.Teaching-learning-based optimization algorithm based on random crossover-self-learning strategy[J].CAAI Transactions on Intelligent Systems,2021,16(2):313-322.[doi:10.11992/tis.201910045]
点击复制

随机交叉-自学策略改进的教与学优化算法

参考文献/References:
[1] RAO R V, SAVSANI V J, VAKHARIA D P. Teaching-learning-based optimization:a novel method for constrained mechanical design optimization problems[J]. Computer-aided design, 2011, 43(3):303-315.
[2] RAO R V, SAVSANI V J, VAKHARIA D P. Teaching-Learning-Based Optimization:an optimization method for continuous non-linear large scale problems[J]. Information sciences, 2012, 183(1):1-15.
[3] RAO R V, PATEL V. Multi-objective optimization of two stage thermoelectric cooler using a modified teaching-learning-based optimization algorithm[J]. Engineering applications of artificial intelligence, 2013, 26(1):430-445.
[4] TUO Shouheng, HE Hong. Solving complex cardinality constrained mean-variance portfolio optimization problems using hybrid HS and TLBO algorithm[J]. Economic Computation and Economic Cybernetics Studies and Research, 2018, 52(3):231-248.
[5] CHINTA S, KOMMADATH R, KOTECHA P. A note on multi-objective improved teaching-learning based optimization algorithm (MO-ITLBO)[J]. Information sciences, 2016, 373:337-350.
[6] YU Dong, HONG Jun, ZHANG Jinhua, et al. Multi-objective individualized-instruction teaching-learning-based optimization algorithm[J]. Applied soft computing, 2018, 62:288-314.
[7] OUYANG Haibin, GAO Liqun, KONG Xiangyong, et al. Teaching-learning based optimization with global crossover for global optimization problems[J]. Applied mathematics and computation, 2015, 265:533-556.
[8] CHEN Debao, ZOU Feng, LI Zheng, et al. An improved teaching-learning-based optimization algorithm for solving global optimization problem[J]. Information sciences, 2015, 297:171-190.
[9] ZOU Feng, WANG Lei, HEI Xinhong, et al. Teaching-learning-based optimization with learning experience of other learners and its application[J]. Applied soft computing, 2015, 37:725-736.
[10] 王培崇, 马玥, 耿明月, 等. 具有小世界邻域结构的教与学优化算法[J]. 计算机科学与探索, 2016, 10(9):1341-1350
WANG Peichong, MA Yue, GENG Mingyue, et al. New teaching-learning-based optimization with neighborhood structure based on small world[J]. Journal of frontiers of computer science and technology, 2016, 10(9):1341-1350
[11] 毕晓君, 王佳荟. 基于混合学习策略的教与学优化算法[J]. 浙江大学学报(工学版), 2017, 51(5):1024-1031
BI Xiaojun, WANG Jiahui. Teaching-learning-based optimization algorithm with hybrid learning strategy[J]. Journal of Zhejiang University (Engineering Science), 2017, 51(5):1024-1031
[12] JI Xiaoyuan, YE Hu, ZHOU Jianxin, et al. An improved teaching-learning-based optimization algorithm and its application to a combinatorial optimization problem in foundry industry[J]. Applied soft computing, 2017, 57:504-516.
[13] YU Kunjie, CHEN Xu, WANG Xin, et al. Parameters identification of photovoltaic models using self-adaptive teaching-learning-based optimization[J]. Energy conversion and management, 2017, 145:233-246.
[14] NIU Peifeng, MA Yunpeng, YAN Shanshan. A modified teaching-learning-based optimization algorithm for numerical function optimization[J]. International journal of machine learning and cybernetics, 2019, 10(6):1357-1371.
[15] SHUKLA A K, SINGH P, VARDHAN M. Neighbour teaching learning based optimization for global optimization problems[J]. Journal of intelligent & fuzzy systems, 2018, 34(3):1583-1594.
[16] 柳缔西子, 范勤勤, 胡志华. 基于混沌搜索和权重学习的教与学优化算法及其应用[J]. 智能系统学报, 2018, 13(5):818-828
LIU Dixizi, FAN Qinqin, HU Zhihua. Teaching-learning-based optimization algorithm based on chaotic search and weighted learning and its application[J]. CAAI transactions on intelligent systems, 2018, 13(5):818-828
[17] 何杰光, 彭志平, 崔得龙, 等. 局部维度改进的教与学优化算法[J]. 浙江大学学报(工学版), 2018, 52(11):2159-2170
HE Jieguang, PENG Zhiping, CUI Delong, et al. Teaching-learning-based optimization algorithm with local dimension improvement[J]. Journal of Zhejiang University (Engineering Science), 2018, 52(11):2159-2170
[18] TSAI H C. Confined teaching-learning-based optimization with variable search strategies for continuous optimization[J]. Information sciences, 2019, 500:34-47.
[19] PICKARD J K, CARRETERO J A, BHAVSAR V C. On the convergence and origin bias of the Teaching-Learning-Based-Optimization algorithm[J]. Applied soft computing, 2016, 46:115-127.
[20] TUO Shouheng, ZHANG Junying, YONG Longquan, et al. A harmony search algorithm for high-dimensional multimodal optimization problems[J]. Digital signal processing, 2015, 46:151-163.
相似文献/References:
[1]康 琦,汪 镭,刘小莉,等.基于群体智能框架理念的遗传算法总体模式描述[J].智能系统学报,2007,2(5):42.
 KANG Qi,WANG Lei,LIU Xiao-li,et al.General mode description genetic algorithms based on a framework of swarm intelligence[J].CAAI Transactions on Intelligent Systems,2007,2():42.
[2]杨东升,康 琦,刘 波,等.面向生产系统的残次品主次成因的群体智能分析[J].智能系统学报,2009,4(6):502.[doi:10.3969/j.issn.1673-4785.2009.06.006]
 YANG Dong-sheng,KANG Qi,LIU Bo,et al.Swarm intelligence analysis of primary and secondary causes of defective products for manufacturing system[J].CAAI Transactions on Intelligent Systems,2009,4():502.[doi:10.3969/j.issn.1673-4785.2009.06.006]
[3]丁科,谭营.GPU通用计算及其在计算智能领域的应用[J].智能系统学报,2015,10(1):1.[doi:10.3969/j.issn.1673-4785.201403072]
 DING Ke,TAN Ying.A review on general purpose computing on GPUs and its applications in computational intelligence[J].CAAI Transactions on Intelligent Systems,2015,10():1.[doi:10.3969/j.issn.1673-4785.201403072]
[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,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]秦全德,程适,李丽,等.人工蜂群算法研究综述[J].智能系统学报,2014,9(2):127.[doi:10.3969/j.issn.1673-4785.201309064]
 QIN Quande,CHENG Shi,LI Li,et al.Artificial bee colony algorithm: a survey[J].CAAI Transactions on Intelligent Systems,2014,9():127.[doi:10.3969/j.issn.1673-4785.201309064]
[6]谭营,郑少秋.烟花算法研究进展[J].智能系统学报,2014,9(5):515.[doi:10.3969/j.issn.1673-4785.201409010]
 TAN Ying,ZHENG Shaoqiu.Recent advances in fireworks algorithm[J].CAAI Transactions on Intelligent Systems,2014,9():515.[doi:10.3969/j.issn.1673-4785.201409010]
[7]柳缔西子,范勤勤,胡志华.基于混沌搜索和权重学习的教与学优化算法及其应用[J].智能系统学报,2018,13(5):818.[doi:10.11992/tis.201705017]
 LIU Dixizi,FAN Qinqin,HU Zhihua.Teaching-learning-based optimization algorithm based on chaotic search and weighted learning and its application[J].CAAI Transactions on Intelligent Systems,2018,13():818.[doi:10.11992/tis.201705017]
[8]顾大强,郑文钢.多移动机器人协同搬运技术综述[J].智能系统学报,2019,14(1):20.[doi:10.11992/tis.201801038]
 GU Daqiang,ZHENG Wengang.Technologies for cooperative transportation by multiple mobile robots[J].CAAI Transactions on Intelligent Systems,2019,14():20.[doi:10.11992/tis.201801038]
[9]李景灿,丁世飞.基于人工鱼群算法的孪生支持向量机[J].智能系统学报,2019,14(6):1121.[doi:10.11992/tis.201905025]
 LI Jingcan,DING Shifei.Twin support vector machine based on artificial fish swarm algorithm[J].CAAI Transactions on Intelligent Systems,2019,14():1121.[doi:10.11992/tis.201905025]
[10]邱华鑫,段海滨,范彦铭,等.鸽群交互模式切换模型及其同步性分析[J].智能系统学报,2020,15(2):334.[doi:10.11992/tis.201904052]
 QIU Huaxin,DUAN Haibin,FAN Yanming,et al.Pigeon flock interaction pattern switching model and its synchronization analysis[J].CAAI Transactions on Intelligent Systems,2020,15():334.[doi:10.11992/tis.201904052]

备注/Memo

收稿日期:2019-10-31。
基金项目:国家自然科学基金项目(11502132);陕西省教育厅重点科研计划项目(20JS021);陕西理工大学校级科研项目(SLG1913)
作者简介:黎延海,讲师,主要研究方向为智能优化算法及应用;雍龙泉,教授,博士,主要研究方向为优化理论与算法设计、智能优化算法;拓守恒,副教授,博士,CCF会员,主要研究方向为智能优化算法、生物信息分析与处理。发表学术论文40余篇
通讯作者:黎延海.E-mail:liyanhai@snut.edu.cn

更新日期/Last Update: 2021-04-25
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