25 citations · 30 across the 9 of their papers we have counts for
3 papers · 1 filter
UCPO: A Universal Constrained Combinatorial Optimization Method via Preference Optimization
Zhanhong Fang, Debing Wang, Jinbiao Chen +2
Neural solvers have demonstrated remarkable success in combinatorial optimization, often surpassing traditional heuristics in speed, solution quality, and generalization. However,…
Preference-Driven Multi-Objective Combinatorial Optimization with Conditional Computation
Mingfeng Fan, Jianan Zhou, Yifeng Zhang +3
Recent deep reinforcement learning methods have achieved remarkable success in solving multi-objective combinatorial optimization problems (MOCOPs) by decomposing them into multipl…
BOPO: Neural Combinatorial Optimization via Best-anchored and Objective-guided Preference Optimization
Zijun Liao, Jinbiao Chen, Debing Wang +2
Neural Combinatorial Optimization (NCO) has emerged as a promising approach for NP-hard problems. However, prevailing RL-based methods suffer from low sample efficiency due to spar…