Algorithm structure optimization by choosing operators in multiobjective genetic local search. - Yuki Tanigaki; Hiroyuki Masuda; Yu Setoguchi; Yusuke Nojima; Hisao Ishibuchi (CEC, 2015)

A Knee-Based EMO Algorithm with an Efficient Method to Update Mobile Reference Points. - Yu Setoguchi; Kaname Narukawa; Hisao Ishibuchi (EMO (1), 2015)

Performance comparison of NSGA-II and NSGA-III on various many-objective test problems. - Hisao Ishibuchi; Ryo Imada; Yu Setoguchi; Yusuke Nojima (CEC, 2016)

How to compare many-objective algorithms under different settings of population and archive sizes. - Hisao Ishibuchi; Yu Setoguchi; Hiroyuki Masuda; Yusuke Nojima (CEC, 2016)

Preference representation using Gaussian functions on a hyperplane in evolutionary multi-objective optimization. - Kaname Narukawa; Yu Setoguchi; Yuki Tanigaki; Markus Olhofer; Bernhard Sendhoff; Hisao Ishibuchi (Soft Comput., 2016)

Hypervolume Subset Selection for Triangular and Inverted Triangular Pareto Fronts of Three-Objective Problems. - Hisao Ishibuchi; Ryo Imada; Yu Setoguchi; Yusuke Nojima (FOGA, 2017)

Reference point specification in hypervolume calculation for fair comparison and efficient search. - Hisao Ishibuchi; Ryo Imada; Yu Setoguchi; Yusuke Nojima (GECCO, 2017)

Performance of Decomposition-Based Many-Objective Algorithms Strongly Depends on Pareto Front Shapes. - Hisao Ishibuchi; Yu Setoguchi; Hiroyuki Masuda; Yusuke Nojima (IEEE Trans. Evol. Comput., 2017)

How to Specify a Reference Point in Hypervolume Calculation for Fair Performance Comparison. - Hisao Ishibuchi; Ryo Imada; Yu Setoguchi; Yusuke Nojima (Evol. Comput., 2018)

Reference Point Specification in Inverted Generational Distance for Triangular Linear Pareto Front. - Hisao Ishibuchi; Ryo Imada; Yu Setoguchi; Yusuke Nojima (IEEE Trans. Evol. Comput., 2018)