9 citations · 34 across the 18 of their papers we have counts for
5 papers · 1 filter
Probing Neural Combinatorial Optimization Models
Zhiqin Zhang, Yining Ma, Zhiguang Cao +1
Neural combinatorial optimization (NCO) has achieved remarkable performance, yet its learned model representations and decision rationale remain a black box. This impedes both acad…
SHIELD: Multi-task Multi-distribution Vehicle Routing Solver with Sparsity and Hierarchy
Yong Liang Goh, Zhiguang Cao, Yining Ma +3
Recent advances toward foundation models for routing problems have shown great potential of a unified deep model for various VRP variants. However, they overlook the complex real-w…
DesignX: Human-Competitive Algorithm Designer for Black-Box Optimization
Hongshu Guo, Zeyuan Ma, Yining Ma +3
Designing effective black-box optimizers is hampered by limited problem-specific knowledge and manual control that spans months for almost every detail. In this paper, we present \…
MetaBox-v2: A Unified Benchmark Platform for Meta-Black-Box Optimization
Zeyuan Ma, Yue-Jiao Gong, Hongshu Guo +11
Meta-Black-Box Optimization (MetaBBO) streamlines the automation of optimization algorithm design through meta-learning. It typically employs a bi-level structure: the meta-level p…
Diversity Optimization for Travelling Salesman Problem via Deep Reinforcement Learning
Qi Li, Zhiguang Cao, Yining Ma +2
Existing neural methods for the Travelling Salesman Problem (TSP) mostly aim at finding a single optimal solution. To discover diverse yet high-quality solutions for Multi-Solution…