正在加载图片...
·370· 智能系统学报 第16卷 gress on Computational Intelligence (Cat.No Proceedings of the 2002 Congress on Evolutionary Com- 98TH8360).Anchorage,.USA,1998:73-79. putation.CEC'02(Cat.No.02TH8600).Honolulu,USA, [20]CLERC M,KENNEDY J.The particle swarm-explo- 2002.1051-1056. sion,stability,and convergence in a multidimensional [30]WANG Hui,WU Zhijian,RAHNAMAYAN S,et al.En- complex space[J].IEEE transactions on evolutionary hancing particle swarm optimization using generalized computation,2002,6(1):58-73. opposition-based learning[J].Information sciences,2011, [21]VENTER G.SOBIESZCZANSKI-SOBIESKI J.Mul- 181(20):4699-4714. tidisciplinary optimization of a transport aircraft wing us- [31]马灿,刘坚,余方平.混合模拟退火的布谷鸟算法研究 ing particle swarm optimization[J].Structural and mul- [.小型微型计算机系统,2016,37(9)2029-2034. tidisciplinary optimization,2004,26:121-131. MA Can,LIU Jian,YU Fangping.Research on cuckoo al- [22]MA Borong,HUA Jun,MA Zhixin,et al.IMOPSO:an gorithm with simulated annealing[J].Journal of Chinese improved multi-objective particle swarm optimization al- computer systems,2016,37(9):2029-2034. gorithm[C]//2016 5th International Conference on Com- [32]CHENG Ran,JIN Yaochu,OLHOFER M,et al.A refer- puter Science and Network Technology (ICCSNT). ence vector guided evolutionary algorithm for many-ob- Changchun,China,2016:376-380. jective optimization[J].IEEE transactions on evolution- [23]QI Changxing,BI Yiming,HAN Huihua,et al.A hybrid ary computation,2016,20(5):773-791. particle swarm optimization algorithm[C]//2017 3rd IEEE [33]CORNE D W,JERRAM N R,KNOWLES J D,et al. International Conference on Computer and Communica- PESA-II:region-based selection in evolutionary multiob- tions (ICCC).Chengdu,China,2017:2187-2190. [24]KENNEDY J.Bare bones particle swarms[Cl//Proceed- jective optimization[C]//Proceedings of the 3rd Annual ings of the 2003 IEEE Swarm Intelligence Symposium. Conference on Genetic and Evolutionary Computation. SIS'03(Cat.No.03EX706).Indianapolis,USA,2003: Morgan Kaufmann Publishers Inc,2001:283-290. 80-87. 作者简介: [25]YUE Caitong,QU Boyang,LIANG Jing.A multiobject- 陈强,硕士研究生,主要研究方向 ive particle swarm optimizer using ring topology for Solv- 为进化计算和多目标优化。 ing multimodal multiobjective problems[J].IEEE transac- tions 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) 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]. 王宇嘉,副教授,博土,主要研究 Computer engineering and design,2015,36(6): 方向为进化计算、群智能和目标优 化。发表学术论文16篇。 1530-1534 [27]LIN Qiuzhen,LI Jianqiang,DU Zhihua,et al.A novel multi-objective particle swarm optimization with mul- tiple 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 梁海娜.硕士研究生,主要研究方 向为进化计算和群智能。 multi-objective particle swarm optimization algorithm based on dynamic boundary search for constrained optim- ization[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/gress on Computational Intelligence (Cat. No. 98TH8360). Anchorage, USA, 1998: 73−79. CLERC M, KENNEDY J. The particle swarm - explo￾sion, stability, and convergence in a multidimensional complex space[J]. IEEE transactions on evolutionary computation, 2002, 6(1): 58–73. [20] VENTER G, SOBIESZCZANSKI-SOBIESKI J. Mul￾tidisciplinary optimization of a transport aircraft wing us￾ing particle swarm optimization[J]. Structural and mul￾tidisciplinary optimization, 2004, 26: 121–131. [21] MA Borong, HUA Jun, MA Zhixin, et al. IMOPSO: an improved multi-objective particle swarm optimization al￾gorithm[C]//2016 5th International Conference on Com￾puter Science and Network Technology (ICCSNT). Changchun, China, 2016: 376−380. [22] QI Changxing, BI Yiming, HAN Huihua, et al. A hybrid particle swarm optimization algorithm[C]//2017 3rd IEEE International Conference on Computer and Communica￾tions (ICCC). Chengdu, China, 2017: 2187−2190. [23] KENNEDY J. Bare bones particle swarms[C]//Proceed￾ings of the 2003 IEEE Swarm Intelligence Symposium. SIS'03 (Cat. No. 03EX706). Indianapolis, USA, 2003: 80−87. [24] YUE Caitong, QU Boyang, LIANG Jing. A multiobject￾ive particle swarm optimizer using ring topology for Solv￾ing multimodal multiobjective problems[J]. IEEE transac￾tions on evolutionary computation, 2018, 22(5): 805–817. [25] 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. [26] LIN Qiuzhen, LI Jianqiang, DU Zhihua, et al. A novel multi-objective particle swarm optimization with mul￾tiple search strategies[J]. European Journal of operational research, 2015, 247(3): 732–744. [27] 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 optim￾ization[J]. Applied soft computing, 2018, 70: 680–700. [28] COELLO C A C, LECHUGA M S. MOPSO: a proposal for multiple objective particle swarm optimization[C]// [29] Proceedings of the 2002 Congress on Evolutionary Com￾putation. CEC'02 (Cat. No. 02TH8600). Honolulu, USA, 2002, 1051−1056. WANG Hui, WU Zhijian, RAHNAMAYAN S, et al. En￾hancing particle swarm optimization using generalized opposition-based learning[J]. Information sciences, 2011, 181(20): 4699–4714. [30] 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 al￾gorithm with simulated annealing[J]. Journal of Chinese computer systems, 2016, 37(9): 2029–2034. [31] CHENG Ran, JIN Yaochu, OLHOFER M, et al. A refer￾ence vector guided evolutionary algorithm for many-ob￾jective optimization[J]. IEEE transactions on evolution￾ary computation, 2016, 20(5): 773–791. [32] CORNE D W, JERRAM N R, KNOWLES J D, et al. PESA-II: region-based selection in evolutionary multiob￾jective optimization[C]//Proceedings of the 3rd Annual Conference on Genetic and Evolutionary Computation. Morgan Kaufmann Publishers Inc, 2001: 283−290. [33] 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。 ·370· 智 能 系 统 学 报 第 16 卷
<<向上翻页
©2008-现在 cucdc.com 高等教育资讯网 版权所有