Cover Image

GLOP: Learning Global Partition and Local Construction for Solving Large-scale Routing Problems in Real-time

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Ye, Haoran, Wang, Jiarui, Liang, Helan, Cao, Zhiguang, Li, Yong, Li, Fanzhang
Format:	Preprint
Published:	2023
Subjects:	Artificial Intelligence Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Hierarchical Learning-based Graph Partition for Large-scale Vehicle Routing Problems
by: Pan, Yuxin, et al.
Published: (2025)

Hybrid-Balance GFlowNet for Solving Vehicle Routing Problems
by: Zhang, Ni, et al.
Published: (2025)

Cross-Problem Learning for Solving Vehicle Routing Problems
by: Lin, Zhuoyi, et al.
Published: (2024)

Adversarial Generative Flow Network for Solving Vehicle Routing Problems
by: Zhang, Ni, et al.
Published: (2025)

An Agentic Framework with LLMs for Solving Complex Vehicle Routing Problems
by: Zhang, Ni, et al.
Published: (2025)

Rethinking Light Decoder-based Solvers for Vehicle Routing Problems
by: Huang, Ziwei, et al.
Published: (2025)

DualOpt: A Dual Divide-and-Optimize Algorithm for the Large-scale Traveling Salesman Problem
by: Zhou, Shipei, et al.
Published: (2025)

Learning to Handle Complex Constraints for Vehicle Routing Problems
by: Bi, Jieyi, et al.
Published: (2024)

Hierarchical Neural Constructive Solver for Real-world TSP Scenarios
by: Goh, Yong Liang, et al.
Published: (2024)

Learning to Solve Compositional Geometry Routing Problems
by: Fan, Mingfeng, et al.
Published: (2026)

VAGPO: Vision-augmented Asymmetric Group Preference Optimization for Graph Routing Problems
by: Liu, Shiyan, et al.
Published: (2025)

Learning Topological Representations with Bidirectional Graph Attention Network for Solving Job Shop Scheduling Problem
by: Zhang, Cong, et al.
Published: (2024)

Graph-of-Thought: Utilizing Large Language Models to Solve Complex and Dynamic Business Problems
by: Li, Ye
Published: (2024)

Enhancing Large-scale UAV Route Planing with Global and Local Features via Reinforcement Graph Fusion
by: Zhou, Tao, et al.
Published: (2024)

ReEvo: Large Language Models as Hyper-Heuristics with Reflective Evolution
by: Ye, Haoran, et al.
Published: (2024)

Bridging Synthetic and Real Routing Problems via LLM-Guided Instance Generation and Progressive Adaptation
by: Zhu, Jianghan, et al.
Published: (2025)

Collaboration! Towards Robust Neural Methods for Routing Problems
by: Zhou, Jianan, et al.
Published: (2024)

RADAR: Learning to Route with Asymmetry-aware DistAnce Representations
by: Yi, Hang, et al.
Published: (2026)

Formally Solving Answer-Construction Problems in Lean
by: Sun, Jialiang, et al.
Published: (2025)

SHIELD: Multi-task Multi-distribution Vehicle Routing Solver with Sparsity and Hierarchy
by: Goh, Yong Liang, et al.
Published: (2025)

PyVRP$^+$: LLM-Driven Metacognitive Heuristic Evolution for Hybrid Genetic Search in Vehicle Routing Problems
by: Malik, Manuj, et al.
Published: (2026)

RRNCO: Towards Real-World Routing with Neural Combinatorial Optimization
by: Son, Jiwoo, et al.
Published: (2025)

Reinforcement Learning for Solving Stochastic Vehicle Routing Problem with Time Windows
by: Iklassov, Zangir, et al.
Published: (2024)

Diversity Optimization for Travelling Salesman Problem via Deep Reinforcement Learning
by: Li, Qi, et al.
Published: (2025)

Solving a Real-World Package Delivery Routing Problem Using Quantum Annealers
by: Osaba, Eneko, et al.
Published: (2024)

Edge-Selector Model Applied for Local Search Neighborhood for Solving Vehicle Routing Problems
by: Herdianto, Bachtiar, et al.
Published: (2025)

Hybrid Node-Destroyer Model with Large Neighborhood Search for Solving the Capacitated Vehicle Routing Problem
by: Herdianto, Bachtiar, et al.
Published: (2025)

An End-to-End Learning Approach for Solving Capacitated Location-Routing Problems
by: Miao, Changhao, et al.
Published: (2025)

LMask: Learn to Solve Constrained Routing Problems with Lazy Masking
by: Li, Tianyou, et al.
Published: (2025)

Towards Efficient Constraint Handling in Neural Solvers for Routing Problems
by: Bi, Jieyi, et al.
Published: (2026)

Large Language Models as End-to-end Combinatorial Optimization Solvers
by: Jiang, Xia, et al.
Published: (2025)

Learn to Relax with Large Language Models: Solving Constraint Optimization Problems via Bidirectional Coevolution
by: Liu, Beidan, et al.
Published: (2025)

AlphaTransit: Learning to Design City-scale Transit Routes
by: Poudel, Bibek, et al.
Published: (2026)

Fennec: Fine-grained Language Model Evaluation and Correction Extended through Branching and Bridging
by: Liang, Xiaobo, et al.
Published: (2024)

Is Mathematical Problem-Solving Expertise in Large Language Models Associated with Assessment Performance?
by: Zhang, Liang, et al.
Published: (2026)

Plan before Solving: Problem-Aware Strategy Routing for Mathematical Reasoning with LLMs
by: Qi, Shihao, et al.
Published: (2025)

Learning to Segment for Vehicle Routing Problems
by: Ouyang, Wenbin, et al.
Published: (2025)

Deep Reinforcement Learning for Solving the Fleet Size and Mix Vehicle Routing Problem
by: Wan, Pengfu, et al.
Published: (2025)

Multi-Objective Infeasibility Diagnosis for Routing Problems Using Large Language Models
by: Li, Kai, et al.
Published: (2025)

Reinforcement Learning Problem Solving with Large Language Models
by: Gholamian, Sina, et al.
Published: (2024)