Zhiguang Cao

Assistant Professor@Singapore Management University·新加坡·OpenReview

研究方向

Neural Combinatorial Optimization · Learning to optimize · Learning for optimization · Neural heuristics · Learning based optimization · Combinatorial Optimization Problem

Zhiguang Cao

Towards Efficient Constraint Handling in Neural Solvers for Routing Problems

Refining Hybrid Genetic Search for CVRP via Reinforcement Learning-Finetuned LLM

RRNCO: Towards Real-World Routing with Neural Combinatorial Optimization

Chain-of-Context Learning: Dynamic Constraint Understanding for Multi-Task VRPs

An Agentic Framework with LLMs for Solving Complex Vehicle Routing Problems

Diffusion-Enhanced GFlowNet for Solving Vehicle Routing Problems

RESCHED: Rethinking Flexible Job Shop Scheduling from a Transformer-based Architecture with Simplified States

Generalizable Heuristic Generation Through LLMs with Meta-Optimization

AGOF: A GFlowNet-Guided 2-Opt Framework for Vehicle Routing Problems

RADAR: Learning to Route with Asymmetry-aware Distance Representations

RAISE the Bar: Ensemble-based Online Reinforcement Learning for Dynamic Workflow Scheduling

UniteFormer: Unifying Node and Edge Modalities in Transformers for Vehicle Routing Problems

Hybrid-Balance GFlowNet for Solving Vehicle Routing Problems

Probing Neural Combinatorial Optimization Models

Rethinking Neural Multi-Objective Combinatorial Optimization via Neat Weight Embedding

Multi-Task Vehicle Routing Solver via Mixture of Specialized Experts under State-Decomposable MDP

Learning Memory-Enhanced Improvement Heuristics for Flexible Job Shop Scheduling

Large Language Models as End-to-end Combinatorial Optimization Solvers

Graph Assisted Offline-Online Deep Reinforcement Learning for Dynamic Workflow Scheduling

Neural Multi-Objective Combinatorial Optimization via Graph-Image Multimodal Fusion

Rethinking Light Decoder-based Solvers for Vehicle Routing Problems

Adversarial Generative Flow Network for Solving Vehicle Routing Problems

LLaMoCo: Instruction Tuning of Large Language Models for Optimization Code Generation

SHIELD: Multi-task Multi-distribution Vehicle Routing Solver with Sparsity and Hierarchy

Meta-Black-Box-Optimization through Offline Q-function Learning

From Global Assessment to Local Selection: Efficiently Solving Traveling Salesman Problems of All Sizes

Efficient Heuristics Generation for Solving Combinatorial Optimization Problems Using Large Language Models

Unveiling Neural Combinatorial Optimization Model Representations Through Probing

Coupling Category Alignment for Graph Domain Adaptation

A Mixed-Curvature based Pre-training Paradigm for Multi-Task Vehicle Routing Solver

Meta-Black-Box-Optimization through Offline Q-function Learning with Mamba Architecture

Continuous Spiking Graph ODE Networks

Decision-making with speculative opponent model-aided value function factorization

SHIELD: Multi-task Multi-distribution Vehicle Routing Solver with Sparsity & Hierarchy in Efficiently Layered Decoder

ML4MILP: A Benchmark Dataset for Machine Learning-based Mixed-Integer Linear Programming

RL4CO: an Extensive Reinforcement Learning for Combinatorial Optimization Benchmark