·470· 智能系统学报 第14卷 USA:ACM,2005:257-264 ary programming[C]//Proceedings Volume 3165,Applic- [5]LILi,WANG Wanliang,XU Xinli.Multi-objective ations of Soft Computing.San Diego,CA,United States: Particle swarm optimization based on global margin rank- SPIE,1997:260-269. ing[J].Information sciences,2017,375:30-47. [14]GONG Maoguo,JIAO Licheng,DU Haifeng,et al.Mul- [6]LIN Qiuzhen,LI Jiangqiang,DU Zhihua,et al.A novel tiobjective immune algorithm with nondominated neigh- multi-objective particle swarm optimization with multiple bor-based selection[J].Evolutionary computation,2008. search strategies[J].European journal of operational re- 16(2:225-255. search,2015,247(3:732-744. [15]STORN R.PRICE K.Differential evolution-a simple [7]DAI Cai,WANG Yuping,YE Miao.A new multi-object- and efficient heuristic for global optimization over con- ive particle swarm optimization algorithm based on decom- tinuous spaces[J].Journal of global optimization,1997, position[J].Information sciences,2015,325:541-557. 11(4:341-359 [8]CHENG Tingli,CHEN Minyou,FLEMING P J,et al.A [16]ZITZLER E,THIELE L,LAUMANNS M,et al.Perform- novel hybrid teaching learning based multi-objective particle swarm optimization[J].Neurocomputing,2017, ance assessment of multiobjective optimizers:an analysis 222:11-25. and review[J].IEEE transactions on evolutionary compu- [9]SU Yixin,CHI Rui.Multi-objective particle swarm-differ- tation,2003,72):117-132. ential evolution algorithm[J].Neural Computing and ap- 作者简介： plications,.2017,28(2):407-418. 钱小宇，男，1992年生，硕士研究 [10]ZITZLER E,LAUMANNS M,THIELE L.SPEA2:Im- 生，主要研究方向为人工智能与模式 proving the strength Pareto evolutionary algorithm for 识别。 multiobjective optimization[M]//GIANNAKOGLOU K C,TSAHALIS D T,PERIAUX J,et al.Evolutionary Methods for Design,Optimisation and Control with Ap- plications to Industrial Problems.Athens,Greece:Interna- tional Center for Numerical Methods in Engineering, 葛洪伟，男，1967年生，教授，博 2002:95-100. 士，博士生导师，主要研究方向为人工 [11]JORDEHI A R.Enhanced leader PSO (ELPSO):a new 智能与模式识别、机器学习、图像处理 与分析等。 PSO variant for solving global optimisation problems[J]. Applied Soft Computing,2015,26:401-417. [12]陈明杰，黄佰川，张旻.混合改进蚁群算法的函数优化 [).智能系统学报，2012,74)：370-376. CHEN Mingjie,HUANG Baichuan,ZHANG Min.Func- 蔡明，男，1962年生，高级工程 师，主要研究方向为计算机软件、网络 tion optimization based on an improved hybrid ACO[J]. 应用的研究。 CAAI transactions on intelligent systems,2012,7(4): 370-376. [13]CHELLAPILLA K,FOGEL D B.Two new mutation op- erators for enhanced search and optimization in evolution-USA: ACM, 2005: 257–264. LI Li, WANG Wanliang, XU Xinli. Multi-objective Particle swarm optimization based on global margin rank￾ing[J]. Information sciences, 2017, 375: 30–47. [5] LIN Qiuzhen, LI Jiangqiang, DU Zhihua, et al. A novel multi-objective particle swarm optimization with multiple search strategies[J]. European journal of operational re￾search, 2015, 247(3): 732–744. [6] DAI Cai, WANG Yuping, YE Miao. A new multi-object￾ive particle swarm optimization algorithm based on decom￾position[J]. Information sciences, 2015, 325: 541–557. [7] CHENG Tingli, CHEN Minyou, FLEMING P J, et al. A novel hybrid teaching learning based multi-objective particle swarm optimization[J]. Neurocomputing, 2017, 222: 11–25. [8] SU Yixin, CHI Rui. Multi-objective particle swarm-differ￾ential evolution algorithm[J]. Neural Computing and ap￾plications, 2017, 28(2): 407–418. [9] ZITZLER E, LAUMANNS M, THIELE L. SPEA2: Im￾proving the strength Pareto evolutionary algorithm for multiobjective optimization[M]//GIANNAKOGLOU K C, TSAHALIS D T, PÉRIAUX J, et al. Evolutionary Methods for Design, Optimisation and Control with Ap￾plications to Industrial Problems. Athens, Greece: Interna￾tional Center for Numerical Methods in Engineering, 2002: 95–100. [10] JORDEHI A R. Enhanced leader PSO (ELPSO): a new PSO variant for solving global optimisation problems[J]. Applied Soft Computing, 2015, 26: 401–417. [11] 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, 2012, 7(4): 370–376. CHEN Mingjie, HUANG Baichuan, ZHANG Min. Func￾tion optimization based on an improved hybrid ACO[J]. CAAI transactions on intelligent systems, 2012, 7(4): 370–376. [12] CHELLAPILLA K, FOGEL D B. Two new mutation op￾erators for enhanced search and optimization in evolution- [13] ary programming[C]//Proceedings Volume 3165, Applic￾ations of Soft Computing. San Diego, CA, United States: SPIE, 1997: 260–269. GONG Maoguo, JIAO Licheng, DU Haifeng, et al. Mul￾tiobjective immune algorithm with nondominated neigh￾bor-based selection[J]. Evolutionary computation, 2008, 16(2): 225–255. [14] STORN R, PRICE K. Differential evolution – a simple and efficient heuristic for global optimization over con￾tinuous spaces[J]. Journal of global optimization, 1997, 11(4): 341–359. [15] ZITZLER E, THIELE L, LAUMANNS M, et al. Perform￾ance assessment of multiobjective optimizers: an analysis and review[J]. IEEE transactions on evolutionary compu￾tation, 2003, 7(2): 117–132. [16] 作者简介： 钱小宇，男，1992 年生，硕士研究 生，主要研究方向为人工智能与模式 识别。 葛洪伟，男，1967 年生，教授，博 士，博士生导师，主要研究方向为人工 智能与模式识别、机器学习、图像处理 与分析等。 蔡明，男，1962 年生，高级工程 师，主要研究方向为计算机软件、网络 应用的研究。 ·470· 智 能 系 统 学 报 第 14 卷