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丁炜超 等: 基于信息共享的改进双归档高维多目标进化算法 1169

Methods in Engineering, 2001. 95–100.
[37] Deb K, Thiele L, Laumanns M, Zitzler E. Scalable multi-objective optimization test problems. In: Proc. of the 2002 Congress on
Evolutionary Computation. Honolulu: IEEE, 2002. 825−830. [doi: 10.1109/CEC.2002.1007032]
[38] Zitzler E, Deb K, Thiele L. Comparison of multiobjective evolutionary algorithms: Empirical results. Evolutionary Computation, 2000,
8(2): 173–195. [doi: 10.1162/106365600568202]
[39] Zitzler E, Thiele L. Multiobjective evolutionary algorithms: A comparative case study and the strength Pareto approach. IEEE Trans. on
Evolutionary Computation, 1999, 3(4): 257–271. [doi: 10.1109/4235.797969]
[40] Li MQ, Grosan C, Yang SX, Liu XH, Yao X. Multiline distance minimization: A visualized many-objective test problem suite. IEEE
Trans. on Evolutionary Computation, 2018, 22(1): 61–78. [doi: 10.1109/TEVC.2017.2655451]
[41] Li K, Chen RZ, Fu GT, Yao X. Two-archive evolutionary algorithm for constrained multiobjective optimization. IEEE Trans. on
Evolutionary Computation, 2019, 23(2): 303–315. [doi: 10.1109/TEVC.2018.2855411]
[42] Deb K, Jain H. An evolutionary many-objective optimization algorithm using reference-point-based nondominated sorting approach, part I:
Solving problems with box constraints. IEEE Trans. on Evolutionary Computation, 2014, 18(4): 577–601. [doi: 10.1109/TEVC.2013.
2281535]
[43] Zitzler E, Künzli S. Indicator-based selection in multiobjective search. In: Proc. of the 8th Int’l Conf. on Parallel Problem Solving from
Nature-PPSN VIII. Birmingham: Springer, 2004. 832–842. [doi: 10.1007/978-3-540-30217-9_84]
[44] Zhang QF, Li H. MOEA/D: A multiobjective evolutionary algorithm based on decomposition. IEEE Trans. on Evolutionary Computation,
2007, 11(6): 712–731. [doi: 10.1109/TEVC.2007.892759]
[45] Emmerich M, Beume N, Naujoks B. An EMO algorithm using the hypervolume measure as selection criterion. In: Proc. of the 3rd Int’l
Conf. on Evolutionary Multi-criterion Optimization. Guanajuato: Springer, 2005. 62–76. [doi: 10.1007/978-3-540-31880-4_5]
[46] Liu Z, Han F, Ling QH, Han H, Jiang J. A many-objective optimization evolutionary algorithm based on hyper-dominance degree. Swarm
and Evolutionary Computation, 2023, 83: 101411. [doi: 10.1016/j.swevo.2023.101411]
[47] Ming F, Gong WY, Wang L. A two-stage evolutionary algorithm with balanced convergence and diversity for many-objective
optimization. IEEE Trans. on Systems, Man, and Cybernetics: Systems, 2022, 52(10): 6222–6234. [doi: 10.1109/TSMC.2022.3143657]
[48] Ishibuchi H, Masuda H, Tanigaki Y, Nojima Y. Modified distance calculation in generational distance and inverted generational distance.
In: Proc. of the 8th Int’l Conf. on Evolutionary Multi-criterion Optimization. Guimarães: Springer, 2015. 110−125. [doi: 10.1007/978-3-
319-15892-1_8]
[49] van Veldhuizen DA. Multiobjective evolutionary algorithms: Classifications, analyses, and new innovations [Ph.D. Thesis]. Wright
Patterson Air Force Base: Air Force Institute of Technology, 1999.

附中文参考文献
[2] 姚曙光, 田红旗, 许平. 重载敞车车体结构轻量化设计. 交通运输工程学报, 2011, 11(1): 31–35, 57. [doi: 10.19818/j.cnki.1671-
1637.2011.01.006]
[6] 李艺辉, 刘作军, 李洁. 基于模糊逻辑 NSGA-III 的开关磁阻发电机多目标优化算法. 计算机工程与科学, 2021, 43(3): 534–541. [doi:
10.3969/j.issn.1007-130X.2021.03.020]
[8] 杨铮, 董亮, 蔡新军. 面向多设备协同场景的实时视频流分析系统. 中国科学: 信息科学, 2023, 53(1): 46–65. [doi: 10.1360/SSI-2021-
0179]
2
[9] 谢承旺, 郭华, 韦伟, 姜磊. MaOEA/d : 一种基于双距离构造的高维多目标进化算法. 软件学报, 2023, 34(4): 1523–1542. http://www.
jos.org.cn/1000-9825/6702.htm [doi: 10.13328/j.cnki.jos.006702]
[14] 蔡星娟, 胡钊鸣, 张志霞, 王茜, 崔志华, 张文生. 基于高维多目标优化的多无人机协同航迹规划. 中国科学: 信息科学, 2021, 51(6):
985–996. [doi: 10.1360/SSI-2020-0218]
[30] 刘卓清, 孙宁, 吴易鸣, 杨桐, 梁潇, 方勇纯. 考虑状态约束的五自由度塔式吊车多目标最优轨迹规划. 中国科学: 信息科学, 2022,
52(3): 521–538. [doi: 10.1360/SSI-2021-0106]

作者简介
丁炜超, 博士, 副教授, 主要研究领域为群体智能与演化计算, 多目标优化算法, 模式识别.
李佳宁, 硕士生, 主要研究领域为群体智能与演化计算.
顾春华, 博士, 教授, 博士生导师, 主要研究领域为云计算, 物联网, 信息安全.
刘佳豪, 硕士生, 主要研究领域为多目标优化算法.
董文波, 博士, 讲师, CCF 专业会员, 主要研究领域为多视图机器学习, 深度高斯过程, 多目标优化.