Hiroyuki SATO (佐藤寛之)

0110100_Ⅰ類（情報系）, 0110000_情報理工学域, The University of Electro-Communications

Optimization | 最適化

Multi-objective Optimization | 多目的最適化

Many-objective Optimization | 多数目的最適化

Evolutionary Computation | 進化計算

Time-series Forecast | 時系列予測

Temporal Hierarchical Memory | 階層時間記憶

ジャーナル論文 - rm_published_papers: International Conference Proceedings 査読済み

Stable Normalization for Preference-based Subset Selection with an Unbounded External Archive

by Hiroyuki SATO

公開済 07/2026

Genetic and Evolutionary Computation Conference (GECCO 2026), to appear

ジャーナル論文 - rm_published_papers: International Conference Proceedings 査読済み

Dominance-Boundary-Based Reference Point Generation for Indicator-Based Multiobjective Optimization

by Hiroyuki SATO

公開済 07/2026

Genetic and Evolutionary Computation Conference (GECCO 2026), to appear

ジャーナル論文 - rm_published_papers: International Conference Proceedings 査読済み

Simultaneous Approximation of Constraint-Specific Pareto Fronts by Constraint-Decomposed Push and Pull Search

by Hiroyuki SATO

公開済 07/2026

Genetic and Evolutionary Computation Conference (GECCO 2026), to appear

ジャーナル論文 - rm_published_papers: International Conference Proceedings 査読済み

Turning Parent Degradation into an Advantage: Archive-Directed Mating for Archive-Based Evolutionary Multi-Objective Optimization

by Hiroyuki SATO

公開済 06/2026

The 2026 IEEE Congress on Evolutionary Computation (CEC2026), The 2026 IEEE World Congress on Computational Intelligence (WCCI2026), to appear

ジャーナル論文 - rm_published_papers: International Conference Proceedings 査読済み

Multi-Point Search Towards Dynamic Multimodal Optimization with Frequent Solution Changes on their Locations, Moving speeds, and Numbers

by Hiroyuki SATO

公開済 06/2026

The 2026 IEEE Congress on Evolutionary Computation (CEC2026), The 2026 IEEE World Congress on Computational Intelligence (WCCI2026), to appear

ジャーナル論文 - rm_published_papers: Scientific Journal 査読済み

Handling Multimodality in Pareto Set Estimation via Cluster-Wise Decomposition

by Hiroyuki SATO

公開済 08/04/2026

Applied Sciences, 16, 8, 3655 - 3655

Multimodal multi-objective optimization problems often exhibit one-to-many mappings, where multiple distinct variable vectors correspond to the same objective vector. This characteristic makes Pareto set (PS) estimation difficult, as conventional inverse modeling approaches assume a one-to-one correspondence. This study proposes a cluster-wise PS estimation framework in the variable space. Known solutions are partitioned into locally monotonic clusters using oscillation detection with an amplitude threshold, and independent response surface models are constructed for each cluster. By estimating PS solutions from multiple cluster-specific models for a given direction vector, the method preserves multimodal structures that conventional approaches fail to capture. Numerical experiments on the multimodal benchmark problems MMF1–8 and LIRCMOP1–2 demonstrate that the proposed method achieves equal or better HV and IGD values than the conventional method, while improving decision-space approximation as measured by IGDX in most test cases and suppressing the generation of dominated solutions.

ジャーナル論文 - rm_published_papers: International Conference Proceedings 査読済み

Transferring Search Dynamics Instead of Solutions for Evolutionary Multi-Objective Optimization

by Hiroyuki SATO

公開済 04/2026

The 10th International Conference on Intelligent Systems, Metaheuristics & Swarm Intelligence (ISMSI2026), to appear

ジャーナル論文 - rm_published_papers: International Conference Proceedings 査読済み

Adaptive Correction-Aware Multi-layer Cortical Learning Algorithm for Forecasting Real-World Time-Series Data

by Hiroyuki SATO

公開済 04/2026

The 10th International Conference on Intelligent Systems, Metaheuristics & Swarm Intelligence (ISMSI2026), to appear

ジャーナル論文 - rm_published_papers: International Conference Proceedings 査読済み

Feature-Aware Probabilistic Partitioning for Distributed Multi-Robot Gaussian Process Exploration

by Hiroyuki SATO

公開済 04/2026

The 10th International Conference on Intelligent Systems, Metaheuristics & Swarm Intelligence (ISMSI2026), to appear

ジャーナル論文 - rm_published_papers: International Conference Proceedings 査読済み

Meta Deep Reinforcement Learning Based on Supervised Learning of Correspondence between Model Parameters and Reward Functions as Externally Conditioned Queries

by Hiroyuki SATO

公開済 03/2026

The 18th International Conference on Agents and Artificial Intelligence (ICAART 2026), 4468 - 4475

Hiroyuki SATO (佐藤 寛之)

0110100_Ⅰ類（情報系）, 0110000_情報理工学域, The University of Electro-Communications

研究業績リスト

Hiroyuki SATO (佐藤寛之)