4 papers
Collaborative Pareto Set Learning in Multiple Multi-Objective Optimization Problems
Chikai Shang, Rongguang Ye, Jiaqi Jiang +1
Pareto Set Learning (PSL) is an emerging research area in multi-objective optimization, focusing on training neural networks to learn the mapping from preference vectors to Pareto…
Pareto Front Shape-Agnostic Pareto Set Learning in Multi-Objective Optimization
Rongguang Ye, Longcan Chen, Wei-Bin Kou +2
Pareto set learning (PSL) is an emerging approach for acquiring the complete Pareto set of a multi-objective optimization problem. Existing methods primarily rely on the mapping of…
Evolutionary Preference Sampling for Pareto Set Learning
Rongguang Ye, Longcan Chen, Jinyuan Zhang +1
Recently, Pareto Set Learning (PSL) has been proposed for learning the entire Pareto set using a neural network. PSL employs preference vectors to scalarize multiple objectives, fa…
Data-Driven Preference Sampling for Pareto Front Learning
Rongguang Ye, Lei Chen, Weiduo Liao +2
Pareto front learning is a technique that introduces preference vectors in a neural network to approximate the Pareto front. Previous Pareto front learning methods have demonstrate…