Zhenkun Wang

URS: A Unified Neural Routing Solver for Cross-Problem Zero-Shot Generalization

ARS: Automatic Routing Solver with Large Language Models

Learning to Reduce Search Space for Generalizable Neural Routing Solver

Fusing LLMs with Scientific Literature for Heuristic Discovery

Rethinking Distance Metric Generalization in Neural Combinatorial Optimization for Vehicle Routing Problems

TS-MOF: Two-Stage Multi-Objective Fine-tuning for Long-Tailed Recognition

Monte Carlo Tree Search for Comprehensive Exploration in LLM-Based Automatic Heuristic Design

Balancing Model Efficiency and Performance: Adaptive Pruner for Long-tailed Data

Few for Many: Tchebycheff Set Scalarization for Many-Objective Optimization

Rethinking Neural Combinatorial Optimization for Vehicle Routing Problems with Different Constraint Tightness Degrees

CaDA: Cross-Problem Routing Solver with Constraint-Aware Dual-Attention

Improving Generalization of Neural Combinatorial Optimization for Vehicle Routing Problems via Test-Time Projection Learning

Learning to Insert for Constructive Neural Vehicle Routing Solver

Boosting Neural Combinatorial Optimization for Large-Scale Vehicle Routing Problems

ICAM: Rethinking Instance-Conditioned Adaptation in Neural Vehicle Routing Solver

MTL-KD: Multi-Task Learning Via Knowledge Distillation for Generalizable Neural Vehicle Routing Solver

Balancing Model Efficiency and Performance: Adaptive Pruner for Long-tailed Data