Cover Image

An End-to-End Deep Reinforcement Learning Approach for Solving the Traveling Salesman Problem with Drones

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Zeng, Taihelong, Lin, Yun, Shi, Yuhe, Li, Yan, Wei, Zhiqing, Ji, Xuanru
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Unsupervised Learning for Solving the Travelling Salesman Problem
by: Min, Yimeng, et al.
Published: (2023)

A Unified Deep Reinforcement Learning Approach for Close Enough Traveling Salesman Problem
by: Fan, Mingfeng, et al.
Published: (2025)

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

Generative Modeling for Robust Deep Reinforcement Learning on the Traveling Salesman Problem
by: Li, Michael, et al.
Published: (2025)

Construct, Merge, Solve & Adapt with Reinforcement Learning for the min-max Multiple Traveling Salesman Problem
by: Rodríguez-Corominas, Guillem, et al.
Published: (2026)

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

Combining Reinforcement Learning and Optimal Transport for the Traveling Salesman Problem
by: Goh, Yong Liang, et al.
Published: (2022)

iMTSP: Solving Min-Max Multiple Traveling Salesman Problem with Imperative Learning
by: Guo, Yifan, et al.
Published: (2024)

Position: Rethinking Post-Hoc Search-Based Neural Approaches for Solving Large-Scale Traveling Salesman Problems
by: Xia, Yifan, et al.
Published: (2024)

Looking Ahead to Avoid Being Late: Solving Hard-Constrained Traveling Salesman Problem
by: Chen, Jingxiao, et al.
Published: (2024)

On Size and Hardness Generalization in Unsupervised Learning for the Travelling Salesman Problem
by: Min, Yimeng, et al.
Published: (2024)

An End-to-End Reinforcement Learning Based Approach for Micro-View Order-Dispatching in Ride-Hailing
by: Yue, Xinlang, et al.
Published: (2024)

Comment on paper: Position: Rethinking Post-Hoc Search-Based Neural Approaches for Solving Large-Scale Traveling Salesman Problems
by: Min, Yimeng
Published: (2024)

Distilling Privileged Information for Dubins Traveling Salesman Problems with Neighborhoods
by: Shin, Min Kyu, et al.
Published: (2024)

Deep Reinforcement Learning for Traveling Purchaser Problems
by: Yuan, Haofeng, et al.
Published: (2024)

Adaptation and Fine-tuning with TabPFN for Travelling Salesman Problem
by: Vu, Nguyen Gia Hien, et al.
Published: (2025)

A Provable Approach for End-to-End Safe Reinforcement Learning
by: Wachi, Akifumi, et al.
Published: (2025)

Spatial-Aware Deep Reinforcement Learning for the Traveling Officer Problem
by: Strauß, Niklas, et al.
Published: (2024)

Training and Simulation of Quadrupedal Robot in Adaptive Stair Climbing for Indoor Firefighting: An End-to-End Reinforcement Learning Approach
by: Huang, Baixiao, et al.
Published: (2026)

End-to-End Deep Learning for Predicting Metric Space-Valued Outputs
by: Zhou, Yidong, et al.
Published: (2025)

DeepTravel: An End-to-End Agentic Reinforcement Learning Framework for Autonomous Travel Planning Agents
by: Ning, Yansong, et al.
Published: (2025)

End-to-End Reinforcement Learning of Curative Curtailment with Partial Measurement Availability
by: Wolf, Hinrikus, et al.
Published: (2024)

Sub-JEPA: Subspace Gaussian Regularization for Stable End-to-End World Models
by: Zhao, Kai, et al.
Published: (2026)

Incorporating Graph Attention Mechanism into Geometric Problem Solving Based on Deep Reinforcement Learning
by: Zhong, Xiuqin, et al.
Published: (2024)

AI2STOW: End-to-End Deep Reinforcement Learning to Construct Master Stowage Plans under Demand Uncertainty
by: Van Twiller, Jaike, et al.
Published: (2025)

Learning to Remember: End-to-End Training of Memory Agents for Long-Context Reasoning
by: Zhang, Kehao, et al.
Published: (2026)

End-to-End Framework Integrating Generative AI and Deep Reinforcement Learning for Autonomous Ultrasound Scanning
by: Elmekki, Hanae, et al.
Published: (2025)

ClustRecNet: A Novel End-to-End Deep Learning Framework for Clustering Algorithm Recommendation
by: Bakhtyari, Mohammadreza, et al.
Published: (2025)

Multi-Resolution End-to-End Deep Neural Network for Optimizing Latency-Accuracy Tradeoff in Autonomous Driving
by: Weng, Qitao, et al.
Published: (2026)

Bridging the Divide: End-to-End Sequence-Graph Learning
by: Chen, Yuen, et al.
Published: (2025)

Deep Reinforcement Learning for Solving Management Problems: Towards A Large Management Mode
by: Jiang, Jinyang, et al.
Published: (2024)

L-MoE: End-to-End Training of a Lightweight Mixture of Low-Rank Adaptation Experts
by: Ji, Shihao, et al.
Published: (2025)

End-To-End Learning of Gaussian Mixture Priors for Diffusion Sampler
by: Blessing, Denis, et al.
Published: (2025)

Solving the Cold Start Problem on One's Own as an End User via Preference Transfer
by: Sato, Ryoma
Published: (2025)

Co-Designing Binarized Transformer and Hardware Accelerator for Efficient End-to-End Edge Deployment
by: Ji, Yuhao, et al.
Published: (2024)

Identifying Functionally Important Features with End-to-End Sparse Dictionary Learning
by: Braun, Dan, et al.
Published: (2024)

End-to-End Learning for Partially-Observed Time Series with PyPOTS
by: Du, Wenjie, et al.
Published: (2026)

Learning to be Smooth: An End-to-End Differentiable Particle Smoother
by: Younis, Ali, et al.
Published: (2025)

OptiProxy-NAS: Optimization Proxy based End-to-End Neural Architecture Search
by: Lyu, Bo, et al.
Published: (2025)

Conditional Rectified Flow-based End-to-End Rapid Seismic Inversion Method
by: Xu, Haofei, et al.
Published: (2026)