1 citations · 1 across the 8 of their papers we have counts for
8 papers
An Evolutionary Algorithm Assisted by an Ensemble of Pareto-Optimal Surrogate Models
Kei Nishihara, Yaochu Jin, Masaya Nakata
An ensemble of surrogate models helps improve the prediction quality and robustness of surrogate models, and in turn, the search performance of surrogate-assisted evolutionary algo…
HCPO: Hierarchical Conductor-Based Policy Optimization in Multi-Agent Reinforcement Learning
Zejiao Liu, Junqi Tu, Yitian Hong +4
In cooperative Multi-Agent Reinforcement Learning (MARL), efficient exploration is crucial for optimizing the performance of joint policy. However, existing methods often update jo…
MO-EMT-NAS: Multi-Objective Continuous Transfer of Architectural Knowledge Between Tasks from Different Datasets
Peng Liao, XiLu Wang, Yaochu Jin +1
Deploying models across diverse devices demands tradeoffs among multiple objectives due to different resource constraints. Arguably, due to the small model trap problem in multi-ob…
An Enhanced Differential Grouping Method for Large-Scale Overlapping Problems
Maojiang Tian, Mingke Chen, Wei Du +2
Large-scale overlapping problems are prevalent in practical engineering applications, and the optimization challenge is significantly amplified due to the existence of shared varia…
A Composite Decomposition Method for Large-Scale Global Optimization
Maojiang Tian, Minyang Chen, Wei Du +3
Cooperative co-evolution (CC) algorithms, based on the divide-and-conquer strategy, have emerged as the predominant approach to solving large-scale global optimization (LSGO) probl…
Diffusion Model-Based Multiobjective Optimization for Gasoline Blending Scheduling
Wenxuan Fang, Wei Du, Renchu He +3
Gasoline blending scheduling uses resource allocation and operation sequencing to meet a refinery's production requirements. The presence of nonlinearity, integer constraints, and…
Knowledge-Assisted Dual-Stage Evolutionary Optimization of Large-Scale Crude Oil Scheduling
Wanting Zhang, Wei Du, Guo Yu +3
With the scaling up of crude oil scheduling in modern refineries, large-scale crude oil scheduling problems (LSCOSPs) emerge with thousands of binary variables and non-linear const…
A Novel Dual-Stage Evolutionary Algorithm for Finding Robust Solutions
Wei Du, Wenxuan Fang, Chen Liang +2
In robust optimization problems, the magnitude of perturbations is relatively small. Consequently, solutions within certain regions are less likely to represent the robust optima w…