Imagen de Portada

Edge-DIRECT: A Deep Reinforcement Learning-based Method for Solving Heterogeneous Electric Vehicle Routing Problem with Time Window Constraints

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Mozhdehi, Arash, Mohammadizadeh, Mahdi, Wang, Xin
Formato:	Preprint
Publicado:	2024
Materias:	Machine Learning Artificial Intelligence
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

SED2AM: Solving Multi-Trip Time-Dependent Vehicle Routing Problem using Deep Reinforcement Learning
por: Mozhdehi, Arash, et al.
Publicado: (2025)

Meta-GCN: A Dynamically Weighted Loss Minimization Method for Dealing with the Data Imbalance in Graph Neural Networks
por: Mohammadizadeh, Mahdi, et al.
Publicado: (2024)

A Curriculum-Based Deep Reinforcement Learning Framework for the Electric Vehicle Routing Problem
por: Daysalilar, Mertcan, et al.
Publicado: (2026)

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

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

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

Deep Reinforcement Learning for Multi-Truck Vehicle Routing Problems with Multi-Leg Demand Routes
por: Levin, Joshua, et al.
Publicado: (2024)

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

Learning to Solve Orienteering Problem with Time Windows and Variable Profits
por: Gao, Songqun, et al.
Publicado: (2026)

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

Reinforcement Learning for Multi-Truck Vehicle Routing Problems
por: Levin, Joshua, et al.
Publicado: (2022)

Deep Reinforcement Learning for Picker Routing Problem in Warehousing
por: Dunn, George, et al.
Publicado: (2024)

GASE: Graph Attention Sampling with Edges Fusion for Solving Vehicle Routing Problems
por: Wang, Zhenwei, et al.
Publicado: (2024)

Demand Acceptance using Reinforcement Learning for Dynamic Vehicle Routing Problem with Emission Quota
por: Najar, Farid, et al.
Publicado: (2026)

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

Deep Reinforcement Learning-Based Approach for a Single Vehicle Persistent Surveillance Problem with Fuel Constraints
por: Mishra, Manav, et al.
Publicado: (2024)

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

Model-Based Safe Reinforcement Learning with Time-Varying State and Control Constraints: An Application to Intelligent Vehicles
por: Zhang, Xinglong, et al.
Publicado: (2021)

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

Efficient Neural Combinatorial Optimization Solver for the Min-max Heterogeneous Capacitated Vehicle Routing Problem
por: Wu, Xuan, et al.
Publicado: (2025)

Enhancing Cross-Problem Vehicle Routing via Federated Learning
por: Meng, Xiangchi, et al.
Publicado: (2026)

An End-to-End Deep Reinforcement Learning Approach for Solving the Traveling Salesman Problem with Drones
por: Zeng, Taihelong, et al.
Publicado: (2025)

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

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

Lifelong Learning with Behavior Consolidation for Vehicle Routing
por: Pei, Jiyuan, et al.
Publicado: (2025)

Neural Deconstruction Search for Vehicle Routing Problems
por: Hottung, André, et al.
Publicado: (2025)

DeepMDV: Global Spatial Matching for Multi-depot Vehicle Routing Problems
por: Nasehi, Saeed, et al.
Publicado: (2024)

Reinforcement Learning-based Approach for Vehicle-to-Building Charging with Heterogeneous Agents and Long Term Rewards
por: Liu, Fangqi, et al.
Publicado: (2025)

RouteExplainer: An Explanation Framework for Vehicle Routing Problem
por: Kikuta, Daisuke, et al.
Publicado: (2024)

WinTSR: A Windowed Temporal Saliency Rescaling Method for Interpreting Time Series Deep Learning Models
por: Islam, Md. Khairul, et al.
Publicado: (2024)

Prompt Learning for Generalized Vehicle Routing
por: Liu, Fei, et al.
Publicado: (2024)

The Edge-of-Reach Problem in Offline Model-Based Reinforcement Learning
por: Sims, Anya, et al.
Publicado: (2024)

PeersimGym: An Environment for Solving the Task Offloading Problem with Reinforcement Learning
por: Metelo, Frederico, et al.
Publicado: (2024)

Towards Generalization-Oriented Models for Vehicle Routing Problems with Mixture-of-Experts
por: Miao, Changhao, et al.
Publicado: (2026)

SynthCharge: An Electric Vehicle Routing Instance Generator with Feasibility Screening to Enable Learning-Based Optimization and Benchmarking
por: Daysalilar, Mertcan, et al.
Publicado: (2026)

GLOP: Learning Global Partition and Local Construction for Solving Large-scale Routing Problems in Real-time
por: Ye, Haoran, et al.
Publicado: (2023)

Is Exploration or Optimization the Problem for Deep Reinforcement Learning?
por: Berseth, Glen
Publicado: (2025)

Keep Rehearsing and Refining: Lifelong Learning Vehicle Routing under Continually Drifting Tasks
por: Pei, Jiyuan, et al.
Publicado: (2026)

NCO4CVRP: Neural Combinatorial Optimization for the Capacitated Vehicle Routing Problem
por: Dihan, Mahir Labib, et al.
Publicado: (2026)

Learning to Deliver: a Foundation Model for the Montreal Capacitated Vehicle Routing Problem
por: Chin, Samuel J. K., et al.
Publicado: (2024)