Zhiguang Cao

45 papers · 2020–2026 · 6 conferences · across top CS/AI conferences

Achievements

🏃 Academic Marathon (5) 🌈 Renaissance Researcher (6) 🐝 Cross-Pollinator (10) 🌉 Interdisciplinary Bridge 🗺️ Taxonomy Completionist (48) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🌍 Conference Polyglot (6) 🤝 Dynamic Duo (18) 👑 Triple Crown 🏆 Grand Slam 🔬 Deep Specialist (13) 🏆 Keyword Champion (7) 📈 Trend Setter 💎 Century Club (42) ⚡ Prolific Year (8) 🔥 Unstoppable (6) 🗃️ Keyword Collector (111)

Conferences

NIPS (15) AAAI (9) ICLR (7) ICML (6) IJCAI (6) UAI (2)

Top co-authors

Yaoxin Wu (19) Wen Song (16) Jie Zhang (15) Yining Ma (10) Jianan Zhou (6) Jinbiao Chen (5) Jiahai Wang (5) Yue-Jiao Gong (5) Cong Zhang (4) Yuan Jiang (4)

Research topics

Optimization (1)

Keywords

vehicle routing problem (11) combinatorial optimization (8) graph neural network (7) traveling salesman problem (7) deep reinforcement learning (7) vehicle routing (4) reinforcement learning (4) evolutionary algorithm (3) black-box optimization (3) neural combinatorial optimization (3) domain generalization (3) attention mechanism (3) instance generation (2) ensemble learning (2) route optimization (2) distribution shift (2) integer programming (2) transformer architecture (2) multi-objective optimization (2) neural solver (2)

Papers

Scale-Net: A Hierarchical U-Net Framework for Cross-Scale Generalization in Multi-Task Vehicle Routing AAAI 2026

Instance Generation for Meta-Black-Box Optimization Through Latent Space Reverse Engineering AAAI 2026

Bridging Synthetic and Real Routing Problems via LLM-Guided Instance Generation and Progressive Adaptation AAAI 2026

DualOpt: A Dual Divide-and-Optimize Algorithm for the Large-scale Traveling Salesman Problem AAAI 2025

Rethinking Neural Multi-Objective Combinatorial Optimization via Neat Weight Embedding ICLR 2025

Preference-based Deep Reinforcement Learning for Historical Route Estimation IJCAI 2025

EFormer: An Effective Edge-based Transformer for Vehicle Routing Problems IJCAI 2025

Coupling Category Alignment for Graph Domain Adaptation IJCAI 2025

Meta-Black-Box-Optimization through Offline Q-function Learning ICML 2025

A Mixed-Curvature based Pre-training Paradigm for Multi-Task Vehicle Routing Solver ICML 2025

SHIELD: Multi-task Multi-distribution Vehicle Routing Solver with Sparsity and Hierarchy ICML 2025

Rethinking Light Decoder-based Solvers for Vehicle Routing Problems ICLR 2025

Graph Assisted Offline-Online Deep Reinforcement Learning for Dynamic Workflow Scheduling ICLR 2025

Neural Multi-Objective Combinatorial Optimization via Graph-Image Multimodal Fusion ICLR 2025

Adversarial Generative Flow Network for Solving Vehicle Routing Problems ICLR 2025

DGL: Dynamic Global-Local Information Aggregation for Scalable VRP Generalization with Self-Improvement Learning IJCAI 2025

ConfigX: Modular Configuration for Evolutionary Algorithms via Multitask Reinforcement Learning AAAI 2025

Deep Reinforcement Learning Guided Improvement Heuristic for Job Shop Scheduling ICLR 2024

ReEvo: Large Language Models as Hyper-Heuristics with Reflective Evolution NIPS 2024

Learning to Handle Complex Constraints for Vehicle Routing Problems NIPS 2024

Collaboration! Towards Robust Neural Methods for Routing Problems NIPS 2024

GLOP: Learning Global Partition and Local Construction for Solving Large-Scale Routing Problems in Real-Time AAAI 2024

Adaptive Stabilization Based on Machine Learning for Column Generation ICML 2024

MVMoE: Multi-Task Vehicle Routing Solver with Mixture-of-Experts ICML 2024

Cross-Problem Learning for Solving Vehicle Routing Problems IJCAI 2024

Learning Topological Representations with Bidirectional Graph Attention Network for Solving Job Shop Scheduling Problem UAI 2024

Multi-view graph contrastive learning for solving vehicle routing problems UAI 2023

Efficient Meta Neural Heuristic for Multi-Objective Combinatorial Optimization NIPS 2023

Neural Multi-Objective Combinatorial Optimization with Diversity Enhancement NIPS 2023

MetaBox: A Benchmark Platform for Meta-Black-Box Optimization with Reinforcement Learning NIPS 2023

Towards Omni-generalizable Neural Methods for Vehicle Routing Problems ICML 2023

Ensemble-based Deep Reinforcement Learning for Vehicle Routing Problems under Distribution Shift NIPS 2023

Learning to Search Feasible and Infeasible Regions of Routing Problems with Flexible Neural k-Opt NIPS 2023

DeepACO: Neural-enhanced Ant Systems for Combinatorial Optimization NIPS 2023

Learning Generalizable Models for Vehicle Routing Problems via Knowledge Distillation NIPS 2022

Learning to Solve Routing Problems via Distributionally Robust Optimization AAAI 2022

Learning Scenario Representation for Solving Two-stage Stochastic Integer Programs ICLR 2022

Efficient Neural Neighborhood Search for Pickup and Delivery Problems IJCAI 2022

Graph Learning Assisted Multi-Objective Integer Programming NIPS 2022

Multi-Decoder Attention Model with Embedding Glimpse for Solving Vehicle Routing Problems AAAI 2021

NeuroLKH: Combining Deep Learning Model with Lin-Kernighan-Helsgaun Heuristic for Solving the Traveling Salesman Problem NIPS 2021

Learning Large Neighborhood Search Policy for Integer Programming NIPS 2021

Learning to Iteratively Solve Routing Problems with Dual-Aspect Collaborative Transformer NIPS 2021

Learning to Dispatch for Job Shop Scheduling via Deep Reinforcement Learning NIPS 2020

AATEAM: Achieving the Ad Hoc Teamwork by Employing the Attention Mechanism AAAI 2020