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Hiroyuki Sato
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Controlling dominance area of solutions and its impact on the performance of MOEAs
H Sato, HE Aguirre, K Tanaka
International conference on evolutionary multi-criterion optimization, 5-20, 2007
3792007
Inverted PBI in MOEA/D and its impact on the search performance on multi and many-objective optimization
H Sato
Proceedings of the 2014 Annual Conference on Genetic and Evolutionary …, 2014
1162014
Self-controlling dominance area of solutions in evolutionary many-objective optimization
H Sato, HE Aguirre, K Tanaka
Asia-Pacific Conference on Simulated Evolution and Learning, 455-465, 2010
782010
Evolutionary many-objective optimization
H Ishibuchi, H Sato
Proceedings of the Genetic and Evolutionary Computation Conference Companion …, 2019
692019
Analysis of inverted PBI and comparison with other scalarizing functions in decomposition based MOEAs
H Sato
Journal of Heuristics 21 (6), 819-849, 2015
622015
Local dominance using polar coordinates to enhance multiobjective evolutionary algorithms
H Sato, HE Aguirre, K Tanaka
Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No …, 2004
582004
Variable space diversity, crossover and mutation in MOEA solving many-objective knapsack problems
H Sato, H Aguirre, K Tanaka
Annals of Mathematics and Artificial Intelligence 68 (4), 197-224, 2013
462013
Local dominance and local recombination in MOEAs on 0/1 multiobjective knapsack problems
H Sato, HE Aguirre, K Tanaka
European Journal of Operational Research 181 (3), 1708-1723, 2007
392007
Pareto partial dominance MOEA and hybrid archiving strategy included CDAS in many-objective optimization
H Sato, HE Aguirre, K Tanaka
IEEE Congress on Evolutionary Computation, 1-8, 2010
372010
Pareto partial dominance MOEA and hybrid archiving strategy included CDAS in many-objective optimization
H Sato, HE Aguirre, K Tanaka
IEEE Congress on Evolutionary Computation, 1-8, 2010
372010
Two-stage non-dominated sorting and directed mating for solving problems with multi-objectives and constraints
M Miyakawa, K Takadama, H Sato
Proceedings of the 15th annual conference on Genetic and evolutionary …, 2013
352013
Genetic diversity and effective crossover in evolutionary many-objective optimization
H Sato, HE Aguirre, K Tanaka
International Conference on Learning and Intelligent Optimization, 91-105, 2011
272011
Improved S-CDAs using crossover controlling the number of crossed genes for many-objective optimization
H Sato, H Aguirre, K Tanaka
Proceedings of the 13th annual conference on Genetic and evolutionary …, 2011
252011
Weight Vector Arrangement Using Virtual Objective Vectors in Decomposition-based MOEA
T Takagi, K Takadama, H Sato
2021 IEEE Congress on Evolutionary Computation (CEC), 1462-1469, 2021
172021
XCSR based on compressed input by deep neural network for high dimensional data
K Matsumoto, R Takano, T Tatsumi, H Sato, T Kovacs, K Takadama
Proceedings of the Genetic and Evolutionary Computation Conference Companion …, 2018
162018
On the locality of dominance and recombination in multiobjective evolutionary algorithms
H Sato, HE Aguirre, K Tanaka
2005 IEEE Congress on Evolutionary Computation 1, 451-458, 2005
142005
Knowledge extraction from XCSR based on dimensionality reduction and deep generative models
M Tadokoro, S Hasegawa, T Tatsumi, H Sato, K Takadama
2019 IEEE Congress on Evolutionary Computation (CEC), 1883-1890, 2019
132019
A distribution control of weight vector set for multi-objective evolutionary algorithms
T Takagi, K Takadama, H Sato
International Conference on Bio-inspired Information and Communication, 70-80, 2019
112019
Evolutionary multi-objective air-conditioning schedule optimization for office buildings
Y Ohta, H Sato
Proceedings of the Genetic and Evolutionary Computation Conference Companion …, 2018
112018
Chain-reaction solution update in MOEA/D and its effects on multi-and many-objective optimization
H Sato
Soft Computing 20 (10), 3803-3820, 2016
112016
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