Replica-Based Low Drop-Out Voltage Regulator with Assistant Power Transistors for Digital VLSI Systems. - Yang Nan 001; Chenchang Zhan; Guanhua Wang; Linjun He; Han Li (ISVLSI, 2018)

A 0.5V 46.2ppm°C CMOS Voltage Reference Based on Compensated ΔVTH with Wide Temperature Range and High PSRR. - Linjun He; Chenchang Zhan; Yang Nan 001; Ning Zhang; Lidan Wang 001; Guofeng Li (NEWCAS, 2018)

A 0.6-V Minimum-Supply, 23.5 ppm/°C Subthreshold CMOS Voltage Reference With 0.45% Variation Coefficient. - Chenyu Huang; Chenchang Zhan; Linjun He; Lidan Wang 001; Yang Nan 001 (IEEE Trans. Circuits Syst. II Express Briefs, 2018)

A Study of the Naïve Objective Space Normalization Method in MOEA/D. - Linjun He; Yang Nan 001; Ke Shang 004; Hisao Ishibuchi (SSCI, 2019)

What is a good direction vector set for the R2-based hypervolume contribution approximation. - Yang Nan 001; Ke Shang 004; Hisao Ishibuchi (GECCO, 2020)

Transformation-based Hypervolume Indicator: A Framework for Designing Hypervolume Variants. - Ke Shang 004; Hisao Ishibuchi; Yang Nan 001; Weiyu Chen (SSCI, 2020)

Reverse Strategy for Non-Dominated Archiving. - Yang Nan 001; Ke Shang 004; Hisao Ishibuchi; Linjun He (IEEE Access, 2020)

A Two-stage Hypervolume Contribution Approximation Method Based on R2 Indicator. - Yang Nan 001; Ke Shang 004; Hisao Ishibuchi; Linjun He (CEC, 2021)

Distance-based subset selection revisited. - Ke Shang 004; Hisao Ishibuchi; Yang Nan 001 (GECCO, 2021)

Improving Local Search Hypervolume Subset Selection in Evolutionary Multi-objective Optimization. - Yang Nan 001; Ke Shang 004; Hisao Ishibuchi; Linjun He (SMC, 2021)

Reference Point Specification for Greedy Hypervolume Subset Selection. - Ke Shang 004; Hisao Ishibuchi; Lie Meng Pang; Yang Nan 001 (SMC, 2021)

A Survey of Normalization Methods in Multiobjective Evolutionary Algorithms. - Linjun He; Hisao Ishibuchi; Anupam Trivedi; Handing Wang; Yang Nan 001; Dipti Srinivasan (IEEE Trans. Evol. Comput., 2021)

Direction Vector Selection for R2-Based Hypervolume Contribution Approximation. - Tianye Shu; Ke Shang 004; Yang Nan 001; Hisao Ishibuchi (PPSN (2), 2022)

Benchmarking Subset Selection from Large Candidate Solution Sets in Evolutionary Multi-objective Optimization. - Ke Shang 004; Tianye Shu; Hisao Ishibuchi; Yang Nan 001; Lie Meng Pang (CoRR, 2022)

Effects of Archive Size on Computation Time and Solution Quality for Multi-Objective Optimization. - Tianye Shu; Ke Shang 004; Hisao Ishibuchi; Yang Nan 001 (CoRR, 2022)

Hypervolume-Optimal μ-Distributions on Line/Plane-Based Pareto Fronts in Three Dimensions. - Ke Shang 004; Hisao Ishibuchi; Weiyu Chen; Yang Nan 001; Weiduo Liao (IEEE Trans. Evol. Comput., 2022)

Effects of External Archives on the Performance of Multi-Objective Evolutionary Algorithms on Real-World Problems. - Yang Nan 001; Tianye Shu; Hisao Ishibuchi (CEC, 2023)

Preference-Based Nonlinear Normalization for Multiobjective Optimization. - Linjun He; Yang Nan 001; Hisao Ishibuchi; Dipti Srinivasan (EMO, 2023)

Performance Evaluation of Multi-objective Evolutionary Algorithms Using Artificial and Real-world Problems. - Hisao Ishibuchi; Yang Nan 001; Lie Meng Pang (EMO, 2023)

Two-Stage Greedy Approximated Hypervolume Subset Selection for Large-Scale Problems. - Yang Nan 001; Hisao Ishibuchi; Tianye Shu; Ke Shang 004 (EMO, 2023)

Partially Degenerate Multi-objective Test Problems. - Lie Meng Pang; Yang Nan 001; Hisao Ishibuchi (EMO, 2023)

Effects of Including Optimal Solutions into Initial Population on Evolutionary Multiobjective Optimization. - Cheng Gong; Yang Nan 001; Lie Meng Pang; Qingfu Zhang 001; Hisao Ishibuchi (GECCO, 2023)

Effects of Objective Space Normalization in Multi-Objective Evolutionary Algorithms on Real-World Problems. - Linjun He; Yang Nan 001; Hisao Ishibuchi; Dipti Srinivasan (GECCO, 2023)

Two-Phase Procedure for Efficiently Removing Dominated Solutions From Large Solution Sets. - Tianye Shu; Yang Nan 001; Ke Shang 004; Hisao Ishibuchi (GECCO, 2023)

Two-Stage Lazy Greedy Inclusion Hypervolume Subset Selection for Large-Scale Problem. - Yang Nan 001; Tianye Shu; Hisao Ishibuchi (SMC, 2023)

Effects of Initialization Methods on the Performance of Multi-Objective Evolutionary Algorithms. - Cheng Gong; Lie Meng Pang; Yang Nan 001; Hisao Ishibuchi; Qingfu Zhang 001 (SMC, 2023)

How to Find a Large Solution Set to Cover the Entire Pareto Front in Evolutionary Multi-Objective Optimization. - Lie Meng Pang; Yang Nan 001; Hisao Ishibuchi (SMC, 2023)

Initial Populations with a Few Heuristic Solutions Significantly Improve Evolutionary Multi-Objective Combinatorial Optimization. - Cheng Gong; Yang Nan 001; Lie Meng Pang; Hisao Ishibuchi; Qingfu Zhang 001 (SSCI, 2023)

Examination of the Multimodal Nature of Multi-Objective Neural Architecture Search. - Cheng Gong; Yang Nan 001; Lie Meng Pang; Hisao Ishibuchi; Qingfu Zhang 001 (SSCI, 2023)

Empirical Hypervolume Optimal µ-Distributions on Complex Pareto Fronts. - Ke Shang 004; Tianye Shu; Guotong Wu; Yang Nan 001; Lie Meng Pang; Hisao Ishibuchi (SSCI, 2023)

Analysis of Partition Methods for Dominated Solution Removal from Large Solution Sets. - Tianye Shu; Yang Nan 001; Ke Shang 004; Hisao Ishibuchi (SSCI, 2023)

Ensemble R2-based Hypervolume Contribution Approximation. - Guotong Wu; Tianye Shu; Yang Nan 001; Ke Shang 004; Hisao Ishibuchi (SSCI, 2023)

Effects of Initialization Methods on the Performance of Surrogate-Based Multiobjective Evolutionary Algorithms. - Jinyuan Zhang; Hisao Ishibuchi; Linjun He; Yang Nan 001 (SSCI, 2023)

Effects of corner weight vectors on the performance of decomposition-based multiobjective algorithms. - Linjun He; Auraham Camacho; Yang Nan 001; Anupam Trivedi; Hisao Ishibuchi; Dipti Srinivasan (Swarm Evol. Comput., 2023)

Effects of Archive Size on Computation Time and Solution Quality for Multiobjective Optimization. - Tianye Shu; Ke Shang 004; Hisao Ishibuchi; Yang Nan 001 (IEEE Trans. Evol. Comput., 2023)

Benchmarking large-scale subset selection in evolutionary multi-objective optimization. - Ke Shang 004; Tianye Shu; Hisao Ishibuchi; Yang Nan 001; Lie Meng Pang (Inf. Sci., 2023)

Relation Between Objective Space Normalization and Weight Vector Scaling in Decomposition-Based Multiobjective Evolutionary Algorithms. - Linjun He; Ke Shang 004; Yang Nan 001; Hisao Ishibuchi; Dipti Srinivasan (IEEE Trans. Evol. Comput., 2023)

An Improved Local Search Method for Large-Scale Hypervolume Subset Selection. - Yang Nan 001; Ke Shang 004; Hisao Ishibuchi; Linjun He (IEEE Trans. Evol. Comput., 2023)

Performance Evaluation of Evolutionary Multi-Objective Algorithms Using Real-World Problems with an Additional Total Constraint Violation Objective. - Yang Nan 001; Hisao Ishibuchi; Tianye Shu (CEC, 2024)

Interactive Final Solution Selection in Multi-Objective Optimization. - Cheng Gong; Yang Nan 001; Tianye Shu; Lie Meng Pang; Hisao Ishibuchi; Qingfu Zhang 001 (CEC, 2024)

Last-X-Generation Archiving Strategy for Multi-Objective Evolutionary Algorithms. - Tianye Shu; Yang Nan 001; Ke Shang 004; Hisao Ishibuchi (CEC, 2024)

Analysis of Real-World Constrained Multi-Objective Problems and Performance Comparison of Multi-Objective Algorithms. - Yang Nan 001; Hisao Ishibuchi; Tianye Shu; Ke Shang 004 (GECCO, 2024)

Gradient-Guided Local Search for IGD/IGDPlus Subset Selection. - Yang Nan 001; Hisao Ishibuchi; Tianye Shu; Ke Shang 004 (GECCO, 2024)

Heuristic Initialization and Knowledge-based Mutation for Large-Scale Multi-Objective 0-1 Knapsack Problems. - Cheng Gong; Yang Nan 001; Lie Meng Pang; Hisao Ishibuchi; Qingfu Zhang 001 (GECCO, 2024)

Performance of NSGA-III on Multi-objective Combinatorial Optimization Problems Heavily Depends on Its Implementations. - Cheng Gong; Yang Nan 001; Lie Meng Pang; Hisao Ishibuchi; Qingfu Zhang 001 (GECCO, 2024)

Learning Pareto Set for Multi-Objective Continuous Robot Control. - Tianye Shu; Ke Shang 004; Cheng Gong; Yang Nan 001; Hisao Ishibuchi (IJCAI, 2024)

Reliability of Indicator-Based Comparison Results of Evolutionary Multi-objective Algorithms. - Lie Meng Pang; Hisao Ishibuchi; Yang Nan 001; Cheng Gong (PPSN (4), 2024)

On the use of the Total Constraint Violation as an Additional Objective in Evolutionary Multi-Objective Optimization. - Yang Nan 001; Hisao Ishibuchi; Tianye Shu; Cheng Gong (SMC, 2024)

GHVC-Net: Hypervolume Contribution Approximation Based on Graph Neural Network. - Guotong Wu; Yang Nan 001; Ke Shang 004; Hisao Ishibuchi (SMC, 2024)

Shape of Feasible Regions of Real-World Multi-Objective Problems. - Yang Nan 001; Hisao Ishibuchi; Tianye Shu (CEC, 2025)

On the Quality of Large Non-dominated Archives. - Ke Shang 004; Tianye Shu; Yang Nan 001; Lie Meng Pang; Hisao Ishibuchi (CEC, 2025)

Performance Analysis of Constrained Evolutionary Multi-objective Optimization Algorithms on Artificial and Real-World Problems. - Yang Nan 001; Hisao Ishibuchi; Lie Meng Pang (EMO (2), 2025)

Small Population Size is Enough in Many Cases with External Archives. - Yang Nan 001; Hisao Ishibuchi; Lie Meng Pang (EMO (2), 2025)

Enhancing NSGA-II with a Knee Point for Constrained Multi-objective Optimization. - Lie Meng Pang; Hisao Ishibuchi; Yang Nan 001 (EMO (1), 2025)

Numerical Analysis of Pareto Set Modeling. - Tianye Shu; Hisao Ishibuchi; Yang Nan 001; Lie Meng Pang (EMO (2), 2025)

Optimal Distributions of Solutions for Maximizing the Minimum Crowding Distance for Two-Objective and Three-Objective Linear Pareto Fronts: Search Behavior Analysis of NSGA-II. - Hisao Ishibuchi; Yang Nan 001; Lie Meng Pang (FOGA, 2025)

R2 Indicator Analysis using the Optimal Distributions of Solutions for R2 and Other Indicators. - Yang Nan 001; Hisao Ishibuchi; Tianye Shu; Ke Shang 004 (GECCO, 2025)

Influence of Subpopulation on the Performance of Coevolutionary Algorithms for Constrained Multiobjective Optimization Problems. - Yanyu Chen; Hisao Ishibuchi; Yang Nan 001 (GECCO, 2025)

Investigation of Training-free Metrics for Multi-objective Neural Architecture Search. - Tianye Shu; Hisao Ishibuchi; Andy Song; Yang Nan 001; Lie Meng Pang (IJCNN, 2025)

Gradient-Guided Local Search for Large-Scale Hypervolume Subset Selection. - Yang Nan 001; Tianye Shu; Hisao Ishibuchi; Ke Shang 004 (IEEE Trans. Evol. Comput., 2025)