PyTorch implementation of Neural Combinatorial Optimization with Reinforcement Learning https://arxiv.org/abs/1611.09940

A PyTorch library for all things Reinforcement Learning (RL) for Combinatorial Optimization (CO)

Recent research papers about Foundation Models for Combinatorial Optimization

Deep Reinforcement Learning for Multiobjective Optimization. Code for this paper

[NeurIPS 2023] DeepACO: Neural-enhanced Ant Systems for Combinatorial Optimization

[NeurIPS 2024] ReEvo: Large Language Models as Hyper-Heuristics with Reflective Evolution

This repo implements our paper, "Learning to Iteratively Solve Routing Problems with Dual-Aspect Collaborative Transformer", which has been accepted at NeurIPS 2021.

[AAAI 2024] GLOP: Learning Global Partition and Local Construction for Solving Large-scale Routing Problems in Real-time

L2O/NCO codes from CIAM Group at SUSTech, Shenzhen, China

This repo implements our paper, "Efficient Neural Neighborhood Search for Pickup and Delivery Problems", which has been accepted as short oral at IJCAI 2022.

[ICML'24 FM-Wild Oral] RouteFinder: Towards Foundation Models for Vehicle Routing Problems

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

The implementation code of our paper "Learning Generalizable Models for Vehicle Routing Problems via Knowledge Distillation", accepted at NeurIPS2022.

This repo implements our paper, "Learning to Search Feasible and Infeasible Regions of Routing Problems with Flexible Neural k-Opt", which has been accepted at NeurIPS 2023.

[IROS 2024] EPH: Ensembling Prioritized Hybrid Policies for Multi-agent Pathfinding

Official implementation of IJCAI'24 paper "Towards Generalizable Neural Solvers for Vehicle Routing Problems via Ensemble with Transferrable Local Policy"

[ICML 2023] Official code for "DevFormer: A Symmetric Transformer for Context-Aware Device Placement"

PARCO: Parallel AutoRegressive Combinatorial Optimization