[1]钱小宇,葛洪伟,蔡明.基于目标空间分解和连续变异的多目标粒子群算法[J].智能系统学报,2019,14(3):464-470.[doi:10.11992/tis.201711015]
 QIAN Xiaoyu,GE Hongwei,CAI Ming.Decomposition and continuous mutation-based multi-objective particle swarm optimization[J].CAAI Transactions on Intelligent Systems,2019,14(3):464-470.[doi:10.11992/tis.201711015]
点击复制

基于目标空间分解和连续变异的多目标粒子群算法

参考文献/References:
[1] KENNEDY J, EBERHART R. Particle swarm optimization[C]//Proceedings of ICNN’95-International Conference on Neural Networks. Perth, WA, Australia, Australia:IEEE, 1995:1942-1948.
[2] 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. Honolulu, HI, USA:IEEE, 2002:1051-1056.
[3] COELLO C A C, PULIDO G T, LECHUGA M S. Handling multiple objectives with particle swarm optimization[J]. IEEE transactions on evolutionary computation, 2004, 8(3):256-279.
[4] RAQUEL C R, NAVAL P C JR. An effective use of crowding distance in multiobjective particle swarm optimization[C]//Proceedings of the 7th Annual Conference Genetic and Evolutionary Computation Washington, DC, USA:ACM, 2005:257-264.
[5] LI Li, WANG Wanliang, XU Xinli. Multi-objective Particle swarm optimization based on global margin ranking[J]. Information sciences, 2017, 375:30-47.
[6] LIN Qiuzhen, LI Jiangqiang, 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.
[7] DAI Cai, WANG Yuping, YE Miao. A new multi-objective particle swarm optimization algorithm based on decomposition[J]. Information sciences, 2015, 325:541-557.
[8] 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.
[9] SU Yixin, CHI Rui. Multi-objective particle swarm-differential evolution algorithm[J]. Neural Computing and applications, 2017, 28(2):407-418.
[10] ZITZLER E, LAUMANNS M, THIELE L. SPEA2:Improving 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 Applications to Industrial Problems. Athens, Greece:International Center for Numerical Methods in Engineering, 2002:95-100.
[11] JORDEHI A R. Enhanced leader PSO (ELPSO):a new 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[J]. 智能系统学报, 2012, 7(4):370-376 CHEN Mingjie, HUANG Baichuan, ZHANG Min. Function optimization based on an improved hybrid ACO[J]. CAAI transactions on intelligent systems, 2012, 7(4):370-376
[13] CHELLAPILLA K, FOGEL D B. Two new mutation operators for enhanced search and optimization in evolutionary programming[C]//Proceedings Volume 3165, Applications of Soft Computing. San Diego, CA, United States:SPIE, 1997:260-269.
[14] GONG Maoguo, JIAO Licheng, DU Haifeng, et al. Multiobjective immune algorithm with nondominated neighbor-based selection[J]. Evolutionary computation, 2008, 16(2):225-255.
[15] STORN R, PRICE K. Differential evolution-a simple and efficient heuristic for global optimization over continuous spaces[J]. Journal of global optimization, 1997, 11(4):341-359.
[16] ZITZLER E, THIELE L, LAUMANNS M, et al. Performance assessment of multiobjective optimizers:an analysis and review[J]. IEEE transactions on evolutionary computation, 2003, 7(2):117-132.
相似文献/References:
[1]蒋建国,吴 琼,夏 娜.自适应粒子群算法求解Agent联盟[J].智能系统学报,2007,2(2):69.
 JIANG Jian-guo,WU Qiong,XIA Na.Solving Agent coalition using adaptive particle swarm optimization algorithm[J].CAAI Transactions on Intelligent Systems,2007,2():69.
[2]王兆伟,肖 扬,刘湘黔.基于粒子群算法的MIMO CDMA平坦衰落信道均衡器[J].智能系统学报,2008,3(1):38.
 WANG Zhao-wei,XIAO Yang,LIU Xiang-qian.Application of particle swarm optimization in MIMO CDMA flat fading channel equalizers[J].CAAI Transactions on Intelligent Systems,2008,3():38.
[3]薛英花,田国会,吴 皓,等.智能空间中的服务机器人路径规划[J].智能系统学报,2010,5(3):260.
 XUE Ying-hua,TIAN Guo-hui,WU Hao,et al.Path planning for service robots in an intelligent space[J].CAAI Transactions on Intelligent Systems,2010,5():260.
[4]王 艳,曾建潮.多目标微粒群优化算法综述[J].智能系统学报,2010,5(5):377.[doi:10.3969/j.issn.1673-4785.2010.05.001]
 WANG Yan,ZENG Jian-chao.A survey of a multiobjective particle swarm optimization algorithm[J].CAAI Transactions on Intelligent Systems,2010,5():377.[doi:10.3969/j.issn.1673-4785.2010.05.001]
[5]马胜蓝,叶东毅.一种带禁忌搜索的粒子并行子群最小约简算法[J].智能系统学报,2011,6(2):132.
 MA Shenglan,YE Dongyi.A minimum reduction algorithm based on parallel particle subswarm optimization with tabu search capability[J].CAAI Transactions on Intelligent Systems,2011,6():132.
[6]秦全德,李丽,程适,等.交互学习的粒子群优化算法[J].智能系统学报,2012,7(6):547.
 QIN Quande,LI Li,CHENG Shi,et al.Interactive learning particle swarm optimization algorithm[J].CAAI Transactions on Intelligent Systems,2012,7():547.
[7]陶新民,徐鹏,刘福荣,等.组合分布估计和差分进化的多目标优化算法[J].智能系统学报,2013,8(1):39.[doi:10.3969/j.issn.1673-4785.201208035]
 TAO Xinmin,XU Peng,LIU Furong,et al.Multi objective optimization algorithm composed of estimation of distribution and differential evolution[J].CAAI Transactions on Intelligent Systems,2013,8():39.[doi:10.3969/j.issn.1673-4785.201208035]
[8]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,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.
[9]孙文新,穆华平.自适应群体结构的粒子群优化算法[J].智能系统学报,2013,8(4):372.[doi:10.3969/j.issn.1673-4785.201211041]
 SUN Wenxin,MU Huaping.Particle swarm optimization based on self-adaptive population structure[J].CAAI Transactions on Intelligent Systems,2013,8():372.[doi:10.3969/j.issn.1673-4785.201211041]
[10]张俊玲,陈增强,张青.基于粒子群优化的Elman神经网络无模型控制[J].智能系统学报,2016,11(1):49.[doi:10.11992/tis.201507025]
 ZHANG Junling,CHEN Zengqiang,ZHANG Qing.Elman model-free control method based on particle swarm optimization algorithm[J].CAAI Transactions on Intelligent Systems,2016,11():49.[doi:10.11992/tis.201507025]

备注/Memo

收稿日期:2017-11-13。
基金项目:江苏省普通高校研究生科研创新计划项目(KYLX16_0781,KYLX16_0782);江苏高校优势学科建设工程资助项目(PAPD).
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。
通讯作者:葛洪伟.E-mail:ghw8601@163.com

更新日期/Last Update: 1900-01-01
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