Two-Layered Weight Vector Specification in Decomposition-Based Multi-Objective Algorithms for Many-Objective Optimization Problems
暂无分享,去创建一个
Hisao Ishibuchi | Yusuke Nojima | Naoki Masuyama | Ryo Imada | H. Ishibuchi | Y. Nojima | Naoki Masuyama | Ryo Imada
[1] Hisao Ishibuchi,et al. Modified Distance Calculation in Generational Distance and Inverted Generational Distance , 2015, EMO.
[2] Nicola Beume,et al. SMS-EMOA: Multiobjective selection based on dominated hypervolume , 2007, Eur. J. Oper. Res..
[3] Maoguo Gong,et al. A Clustering-Based Evolutionary Algorithm for Many-Objective Optimization Problems , 2019, IEEE Transactions on Evolutionary Computation.
[4] Mitsuo Gen,et al. Specification of Genetic Search Directions in Cellular Multi-objective Genetic Algorithms , 2001, EMO.
[5] Hisao Ishibuchi,et al. Reference Point Specification in Inverted Generational Distance for Triangular Linear Pareto Front , 2018, IEEE Transactions on Evolutionary Computation.
[6] Kalyanmoy Deb,et al. An Evolutionary Many-Objective Optimization Algorithm Using Reference-Point-Based Nondominated Sorting Approach, Part I: Solving Problems With Box Constraints , 2014, IEEE Transactions on Evolutionary Computation.
[7] Beatrice M. Ombuki-Berman,et al. A Scalability Study of Many-Objective Optimization Algorithms , 2018, IEEE Transactions on Evolutionary Computation.
[8] Qingfu Zhang,et al. An Evolutionary Many-Objective Optimization Algorithm Based on Dominance and Decomposition , 2015, IEEE Transactions on Evolutionary Computation.
[9] Tapabrata Ray,et al. A Decomposition-Based Evolutionary Algorithm for Many Objective Optimization , 2015, IEEE Transactions on Evolutionary Computation.
[10] Hisao Ishibuchi,et al. Reference point specification in hypervolume calculation for fair comparison and efficient search , 2017, GECCO.
[11] Xin Yao,et al. A New Dominance Relation-Based Evolutionary Algorithm for Many-Objective Optimization , 2016, IEEE Transactions on Evolutionary Computation.
[12] Saúl Zapotecas Martínez,et al. On the low-discrepancy sequences and their use in MOEA/D for high-dimensional objective spaces , 2015, 2015 IEEE Congress on Evolutionary Computation (CEC).
[13] Zhang Yi,et al. IGD Indicator-Based Evolutionary Algorithm for Many-Objective Optimization Problems , 2018, IEEE Transactions on Evolutionary Computation.
[14] Marco Laumanns,et al. Scalable multi-objective optimization test problems , 2002, Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600).
[15] Hisao Ishibuchi,et al. A Study on Performance Evaluation Ability of a Modified Inverted Generational Distance Indicator , 2015, GECCO.
[16] Hisao Ishibuchi,et al. Performance of Decomposition-Based Many-Objective Algorithms Strongly Depends on Pareto Front Shapes , 2017, IEEE Transactions on Evolutionary Computation.
[17] Carlos A. Coello Coello,et al. A Study of the Parallelization of a Coevolutionary Multi-objective Evolutionary Algorithm , 2004, MICAI.
[18] Hisao Ishibuchi,et al. How to Specify a Reference Point in Hypervolume Calculation for Fair Performance Comparison , 2018, Evolutionary Computation.
[19] Lothar Thiele,et al. Multiobjective Optimization Using Evolutionary Algorithms - A Comparative Case Study , 1998, PPSN.
[20] Qingfu Zhang,et al. MOEA/D: A Multiobjective Evolutionary Algorithm Based on Decomposition , 2007, IEEE Transactions on Evolutionary Computation.
[21] Hisao Ishibuchi,et al. Comparison of Hypervolume, IGD and IGD+ from the Viewpoint of Optimal Distributions of Solutions , 2019, EMO.