Imagen de Portada

SED2AM: Solving Multi-Trip Time-Dependent Vehicle Routing Problem using Deep Reinforcement Learning

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Mozhdehi, Arash, Wang, Yunli, Sun, Sun, Wang, Xin
Formato:	Preprint
Publicado:	2025
Materias:	Artificial Intelligence Machine Learning
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Edge-DIRECT: A Deep Reinforcement Learning-based Method for Solving Heterogeneous Electric Vehicle Routing Problem with Time Window Constraints
por: Mozhdehi, Arash, et al.
Publicado: (2024)

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)

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

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

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

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

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

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

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

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

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

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

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

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

TripCast: Pre-training of Masked 2D Transformers for Trip Time Series Forecasting
por: Liao, Yuhua, et al.
Publicado: (2024)

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

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)

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)

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

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

Multi-Task Learning for Routing Problem with Cross-Problem Zero-Shot Generalization
por: Liu, Fei, et al.
Publicado: (2024)

A Practical Introduction to Deep Reinforcement Learning
por: Sun, Yinghan, et al.
Publicado: (2025)

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

Enhancing LLMs for Physics Problem-Solving using Reinforcement Learning with Human-AI Feedback
por: Anand, Avinash, et al.
Publicado: (2024)

Networked Restless Multi-Arm Bandits with Reinforcement Learning
por: Zhang, Hanmo, et al.
Publicado: (2025)

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

Improving Generalization of Neural Vehicle Routing Problem Solvers Through the Lens of Model Architecture
por: Xiao, Yubin, et al.
Publicado: (2024)

Representation over Routing: Diagnosing Temporal Routing Pathologies in Multi-Timescale PPO
por: Sun, Jing
Publicado: (2026)

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

Learning to Insert for Constructive Neural Vehicle Routing Solver
por: Luo, Fu, et al.
Publicado: (2025)

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

DPN: Decoupling Partition and Navigation for Neural Solvers of Min-max Vehicle Routing Problems
por: Zheng, Zhi, et al.
Publicado: (2024)

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

Broad Critic Deep Actor Reinforcement Learning for Continuous Control
por: Thalagala, Shiron, et al.
Publicado: (2024)

Plasticine: Accelerating Research in Plasticity-Motivated Deep Reinforcement Learning
por: Yuan, Mingqi, et al.
Publicado: (2025)

Multi-fidelity Reinforcement Learning Control for Complex Dynamical Systems
por: Sun, Luning, et al.
Publicado: (2025)

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)