[1] FLEMING P J, PURSHOUSE R C, LYGOE R J.Many objective optimization:an engineering design perspective[C]//Proceedings of International Conference on Evolutionary Multi-Criterion Optimization.Berlin, Germany:Springer, 2005:14-32. [2] MIN A T W, ONG Y S, GUPTA A, et al.Multiproblem surrogates:transfer evolutionary multiobjective optimization of computationally expensive problems[J].IEEE Transactions on Evolutionary Computation, 2019, 23(1):15-28. [3] CHENG R, RODEMANN T, FISCHER M, et al.Evolutionary many-objective optimization of hybrid electric vehicle control:from general optimization to preference articulation[J].IEEE Transactions on Emerging Topics in Computational Intelligence, 2017, 1(2):97-111. [4] WANG H D, HE S, YAO X.Nadir point estimation for many-objective optimization problems based on emphasized critical regions[J].Soft Computing, 2017, 21(9):2283-2295. [5] CHUGH T, SINDHYA K, MIETTINEN K, et al.Surrogate-assisted evolutionary multiobjective shape optimization of an air intake ventilation system[C]//Proceedings of IEEE Congress on Evolutionary Computation.Washington D.C., USA:IEEE Press, 2017:1541-1548. [6] JIN Y C, WANG H D, CHUGH T, et al.Data-driven evolutionary optimization:an overview and case studies[J].IEEE Transactions on Evolutionary Computation, 2019, 23(3):442-458. [7] CHUGH T, JIN Y C, MIETTINEN K, et al.A surrogate-assisted reference vector guided evolutionary algorithm for computationally expensive many-objective optimization[J].IEEE Transactions on Evolutionary Computation, 2018, 22(1):129-142. [8] SUN C L, JIN Y C, ZENG J C, et al.A two-layer surrogate-assisted particle swarm optimization algorithm[J].Soft Computing, 2015, 19(6):1461-1475. [9] CLARKE S M, GRIEBSCH J H, SIMPSON T W.Analysis of support vector regression for approximation of complex engineering analyses[J].Journal of Mechanical Design, 2005, 127(6):1077-1087. [10] LUO J P, GUPTA A, ONG Y S, et al.Evolutionary optimization of expensive multiobjective problems with co-sub-Pareto front Gaussian process surrogates[J].IEEE Transactions on Cybernetics, 2019, 49(5):1708-1721. [11] GASPAR-CUNHA A, VIEIRA A.A multi-objective evolutionary algorithm using neural networks to approximate fitness evaluations[J].International Journal of Computing System Signals, 2005, 6(1):18-36. [12] LI F, CAI X W, GAO L, et al.A surrogate-assisted multiswarm optimization algorithm for high-dimensional computationally expensive problems[J].IEEE Transactions on Cybernetics, 2021, 51(3):1390-1402. [13] LIU B, ZHANG Q F, GIELEN G G E.A Gaussian process surrogate model assisted evolutionary algorithm for medium scale expensive optimization problems[J].IEEE Transactions on Evolutionary Computation, 2013, 18(2):180-192. [14] TIAN J, TAN Y, ZENG J C, et al.Multiobjective infill criterion driven Gaussian process-assisted particle swarm optimization of high-dimensional expensive problems[J].IEEE Transactions on Evolutionary Computation, 2019, 23(3):459-472. [15] GOEL T, HAFTKA R T, SHYY W, et al.Ensemble of surrogates[J].Structural and Multidisciplinary Optimization, 2007, 33(3):199-216. [16] TANG Y F, CHEN J Q, WEI J H.A surrogate-based particle swarm optimization algorithm for solving optimization problems with expensive black box functions[J].Engineering Optimization, 2013, 45(5):557-576. [17] WANG H D, JIN Y C, DOHERTY J.Committee-based active learning for surrogate-assisted particle swarm optimization of expensive problems[J].IEEE Transactions on Cybernetics, 2017, 47(9):2664-2677. [18] HABIB A, SINGH H K, CHUGH T, et al.A multiple surrogate assisted decomposition-based evolutionary algorithm for expensive multi/many-objective optimization[J].IEEE Transactions on Evolutionary Computation, 2019, 23(6):1000-1014. [19] ROSALES-PÉREZ A, COELLO C A C, GONZALEZ J A, et al.A hybrid surrogate-based approach for evolutionary multi-objective optimization[C]//Proceedings of IEEE Congress on Evolutionary Computation.Washington D.C., USA:IEEE Press, 2013:2548-2555. [20] 魏锋涛, 卢凤仪.融合核函数在改进径向基代理模型中的应用[J].计算机工程与应用, 2019, 55(7):58-65. WEI F T, LU F Y.Application of hybrid kernel function in improved radial basis function metamodel[J].Computer Engineering and Applications, 2019, 55(7):58-65.(in Chinese) [21] EBERHART R, KENNEDY J.A new optimizer using particle swarm theory[C]//Proceedings of the 6th International Symposium on Micro Machine and Human Science.Washington D.C., USA:IEEE Press, 1995:39-43. [22] BROWN G, WYATT J, TINO P.Managing diversity in regression ensembles[J].Journal of Machine Learning Research, 2005, 6:1621-1650. [23] 王旭仁, 马慧珍, 冯安然, 等.基于信息增益与主成分分析的网络入侵检测方法[J].计算机工程, 2019, 45(6):175-180. WANG X R, MA H Z, FENG A R, et al.Network intrusion detection method based on information gain and principal components analysis[J].Computer Engineering, 2019, 45(6):175-180.(in Chinese) [24] NEBRO A J, DURILLO J J, GARCIA-NIETO J, et al.SMPSO:a new PSO-based metaheuristic for multi-objective optimization[C]//Proceedings of IEEE Symposium on Computational Intelligence in Multi-Criteria Decision-Making.Washington D.C., USA:IEEE Press, 2009:66-73. [25] DEB K, PRATAP A, AGARWAL S, et al.A fast and elitist multiobjective genetic algorithm:NSGAII[J].IEEE Transactions on Evolutionary Computation, 2002, 6(2):182-197. [26] ZHANG Q F, LI H.MOEA/D:a multiobjective evolutionary algorithm based on decomposition[J].IEEE Transactions on Evolutionary Computation, 2007, 11(6):712-731. [27] EMMERICH M T M, GIANNAKOGLOU K C, NAUJOKS B.Single-and multiobjective evolutionary optimization assisted by Gaussian random field metamodels[J].IEEE Transactions on Evolutionary Computation, 2006, 10(4):421-439. |