[1]陈强,王宇嘉,梁海娜,等.目标空间映射策略的高维多目标粒子群优化算法[J].智能系统学报,2021,16(2):362-370.[doi:10.11992/tis.202006042]
 CHEN Qiang,WANG Yujia,LIANG Haina,et al.Multi-objective particle swarm optimization algorithm based on an objective space papping strategy[J].CAAI Transactions on Intelligent Systems,2021,16(2):362-370.[doi:10.11992/tis.202006042]
点击复制

目标空间映射策略的高维多目标粒子群优化算法

参考文献/References:
[1] ISHIBUCHI H, TSUKAMOTO N, NOJIMA Y. Evolutionary many-objective optimization:a short review[C]//2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence). Hong Kong, China, 2008:266-271.
[2] 刘建昌, 李飞, 王洪海, 等. 进化高维多目标优化算法研究综述[J]. 控制与决策, 2018, 33(5):879-887
LIU Jianchang, LI Fei, WANG Honghai, et al. Survey on evolutionary many-objective optimization algorithms[J]. Control and decision, 2018, 33(5):879-887
[3] DEB K, PRATAP A, AGARWAL S, et al. A fast and elitist multiobjective genetic algorithm:NSGA-II[J]. IEEE transactions on evolutionary computation, 2002, 6(2):182-197.
[4] DEB K, JAIN H. An evolutionary many-objective optimization algorithm using reference-point-based nondominated sorting approach, Part I:solving problems with box constraints[J]. IEEE transactions on evolutionary computation, 2014, 18(4):577-601.
[5] 汤恺祥, 许峰. 基于大数据聚类的改进NSGA-Ⅲ算法[J]. 信息记录材料, 2020, 21(5):109-112
TANG Kaixiang, XU Feng. Improved NSGA-III algorithm based on big data clustering[J]. Information recording materials, 2020, 21(5):109-112
[6] ZOU Juan, FU Liuwei, ZHENG Jinhua, et al. A many-objective evolutionary algorithm based on rotated grid[J]. Applied soft computing, 2018, 67:596-609.
[7] LIN Qiuzhen, LIU Songbai, TANG Chaoyu, et al. Particle swarm optimization with a balanceable fitness estimation for many-objective optimization problems[J]. IEEE transactions on evolutionary computation, 2018, 22(1):32-46.
[8] ZHANG Qingfu, LI Hui. MOEA/D:a multiobjective evolutionary algorithm based on decomposition[J]. IEEE transactions on evolutionary computation, 2008, 11(6):712-731.
[9] LIU Hailin, GU Fangqing, ZHANG Qingfu. Decomposition of a multiobjective optimization problem into a number of simple multiobjective subproblems[J]. IEEE transactions on evolutionary computation, 2014, 18(3):450-455.
[10] LI Ke, DEB K, ZHANG Qingfu, et al. An evolutionary many-objective optimization algorithm based on dominance and decomposition[J]. IEEE transactions on evolutionary computation, 2015, 19(5):694-716.
[11] LIU Songbai, LIN Qiuzhen, TAN K C, et al. A fuzzy decomposition-based Multi/many-objective evolutionary algorithm[J]. IEEE transactions on cybernetics, 2020:1-15.
[12] ZITZLER E, KüNZLI S. Indicator-based selection in multiobjective search[C]//International Conference on Parallel Problem Solving from Nature. Berlin, Heidelberg:Springer, 2004:832-842.
[13] BADER J, ZITZLER E. HypE:an algorithm for fast hypervolume-based many-objective optimization[J]. Evolutionary computation, 2011, 19(1):45-76.
[14] MENCHACA-MENDEZ A, COELLO C A C. GDE-MOEA:a new MOEA based on the generational distance indicator and ε-dominance[C]//2015 IEEE Congress on Evolutionary Computation (CEC). Sendai, Japan:IEEE, 2015:947-955.
[15] TIAN Ye, CHENG Ran, ZHANG Xingyi, et al. An indicator-based multiobjective evolutionary algorithm with reference point adaptation for better versatility[J]. IEEE transactions on evolutionary computation, 2018, 22(4):609-622.
[16] LI Fei, CHENG Ran, LIU Jianchang, et al. A two-stage R2 indicator based evolutionary algorithm for many-objective optimization[J]. Applied soft computing, 2018, 67:245-260.
[17] LI Miqing, YANG Shengxiang, LIU Xiaohui. Bi-goal evolution for many-objective optimization problems[J]. Artificial intelligence, 2015, 228:45-65.
[18] KENNEDY J, EBERHART R. Particle swarm optimization[C]//Proceedings of ICNN’95-International Conference on Neural Network. Perth, Australia, 1995:1942-1948.
[19] SHI Y, EBERHART R C. A modified particle swarm optimizer[C]//1998 IEEE International Conference on Evolutionary Computation Proceedings. IEEE World Congress on Computational Intelligence (Cat. No. 98TH8360). Anchorage, USA, 1998:73-79.
[20] CLERC M, KENNEDY J. The particle swarm-explosion, stability, and convergence in a multidimensional complex space[J]. IEEE transactions on evolutionary computation, 2002, 6(1):58-73.
[21] VENTER G, SOBIESZCZANSKI-SOBIESKI J. Multidisciplinary optimization of a transport aircraft wing using particle swarm optimization[J]. Structural and multidisciplinary optimization, 2004, 26:121-131.
[22] MA Borong, HUA Jun, MA Zhixin, et al. IMOPSO:an improved multi-objective particle swarm optimization algorithm[C]//20165th International Conference on Computer Science and Network Technology (ICCSNT). Changchun, China, 2016:376-380.
[23] QI Changxing, BI Yiming, HAN Huihua, et al. A hybrid particle swarm optimization algorithm[C]//20173rd IEEE International Conference on Computer and Communications (ICCC). Chengdu, China, 2017:2187-2190.
[24] KENNEDY J. Bare bones particle swarms[C]//Proceedings of the 2003 IEEE Swarm Intelligence Symposium. SIS’03(Cat. No. 03EX706). Indianapolis, USA, 2003:80-87.
[25] YUE Caitong, QU Boyang, LIANG Jing. A multiobjective particle swarm optimizer using ring topology for Solving multimodal multiobjective problems[J]. IEEE transactions on evolutionary computation, 2018, 22(5):805-817.
[26] 侯翔, 蒲国林. 协同粒子群优化算法的改进与仿真[J]. 计算机工程与设计, 2015, 36(6):1530-1534
HOU Xiang, PU Guolin. Improvement of its cooperative particle swarm optimization algorithm and simulation[J]. Computer engineering and design, 2015, 36(6):1530-1534
[27] LIN Qiuzhen, LI Jianqiang, DU Zhihua, et al. A novel multi-objective particle swarm optimization with multiple search strategies[J]. European Journal of operational research, 2015, 247(3):732-744.
[28] ZAIN M Z B M, KANESAN J, CHUAH J H, et al. A multi-objective particle swarm optimization algorithm based on dynamic boundary search for constrained optimization[J]. Applied soft computing, 2018, 70:680-700.
[29] COELLO C A C, LECHUGA M S. MOPSO:a proposal for multiple objective particle swarm optimization[C]//Proceedings of the 2002 Congress on Evolutionary Computation. CEC’02(Cat. No. 02TH8600). Honolulu, USA, 2002, 1051-1056.
[30] WANG Hui, WU Zhijian, RAHNAMAYAN S, et al. Enhancing particle swarm optimization using generalized opposition-based learning[J]. Information sciences, 2011, 181(20):4699-4714.
[31] 马灿, 刘坚, 余方平. 混合模拟退火的布谷鸟算法研究[J]. 小型微型计算机系统, 2016, 37(9):2029-2034
MA Can, LIU Jian, YU Fangping. Research on cuckoo algorithm with simulated annealing[J]. Journal of Chinese computer systems, 2016, 37(9):2029-2034
[32] CHENG Ran, JIN Yaochu, OLHOFER M, et al. A reference vector guided evolutionary algorithm for many-objective optimization[J]. IEEE transactions on evolutionary computation, 2016, 20(5):773-791.
[33] CORNE D W, JERRAM N R, KNOWLES J D, et al. PESA-II:region-based selection in evolutionary multiobjective optimization[C]//Proceedings of the 3rd Annual Conference on Genetic and Evolutionary Computation. Morgan Kaufmann Publishers Inc, 2001:283-290.
相似文献/References:
[1]张江强,赵宁,刘文奇.具有两类请求的云计算中心服务器数量的优化[J].智能系统学报,2017,12(5):601.[doi:10.11992/tis.201703042]
 ZHANG Jiangqiang,ZHAO Ning,LIU Wenqi.Optimization of the number of servers in a cloud computation center with two demand classes[J].CAAI Transactions on Intelligent Systems,2017,12():601.[doi:10.11992/tis.201703042]
[2]田勇,王洪光,潘新安,等.协作机器人的构型分析研究[J].智能系统学报,2019,14(2):217.[doi:10.11992/tis.201806044]
 TIAN Yong,WANG Hongguang,PAN Xinan,et al.Research on configuration analysis of collaborative robots[J].CAAI Transactions on Intelligent Systems,2019,14():217.[doi:10.11992/tis.201806044]

备注/Memo

收稿日期:2020-06-24。
基金项目:国家自然科学基金项目(61403249)
作者简介:陈强,硕士研究生,主要研究方向为进化计算和多目标优化;王宇嘉,副教授,博士,主要研究方向为进化计算、群智能和目标优化。发表学术论文16篇;梁海娜,硕士研究生,主要研究方向为进化计算和群智能
通讯作者:王宇嘉.E-mail:yjwangamber@sues.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