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Disambiguation of "Masuda, Hiroyuki"

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Common properties of scalable multiobjective problems and a new framework of test problems.

, , and . CEC, page 3011-3018. IEEE, (2016)

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Hiroyuki Tan

Hiroyuki Kobayashi

Hiroyuki Okamuro

Hiroyuki Takada

Hiroyuki Isobe

 

Other publications of authors with the same name

Relation Between Weight Vectors and Solutions in MOEA/D., , , and . SSCI, page 861-868. IEEE, (2015)Performance of Decomposition-Based Many-Objective Algorithms Strongly Depends on Pareto Front Shapes., , , and . IEEE Trans. Evol. Comput., 21 (2): 169-190 (2017)Algorithm structure optimization by choosing operators in multiobjective genetic local search., , , , and . CEC, page 854-861. IEEE, (2015)Common properties of scalable multiobjective problems and a new framework of test problems., , and . CEC, page 3011-3018. IEEE, (2016)Sensitivity of performance evaluation results by inverted generational distance to reference points., , and . CEC, page 1107-1114. IEEE, (2016)Modified Distance Calculation in Generational Distance and Inverted Generational Distance., , , and . EMO (2), volume 9019 of Lecture Notes in Computer Science, page 110-125. Springer, (2015)Distance-Based Analysis of Crossover Operators for Many-Objective Knapsack Problems., , , and . PPSN, volume 8672 of Lecture Notes in Computer Science, page 600-610. Springer, (2014)Meta-level multi-objective formulations of set optimization for multi-objective optimization problems: multi-reference point approach to hypervolume maximization., , and . GECCO (Companion), page 89-90. ACM, (2014)Visual examination of the behavior of EMO algorithms for many-objective optimization with many decision variables., , and . IEEE Congress on Evolutionary Computation, page 2633-2640. IEEE, (2014)A Study on Performance Evaluation Ability of a Modified Inverted Generational Distance Indicator., , and . GECCO, page 695-702. ACM, (2015)