Online Control of Adaptive Large Neighborhood Search using Deep Reinforcement Learning

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Reijnen, Robbert, Zhang, Yingqian, Lau, Hoong Chuin, Bukhsh, Zaharah
Format:	Preprint
Published:	2022
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Job Shop Scheduling Benchmark: Environments and Instances for Learning and Non-learning Methods
by: Reijnen, Robbert, et al.
Published: (2023)

Graph-Supported Dynamic Algorithm Configuration for Multi-Objective Combinatorial Optimization
by: Reijnen, Robbert, et al.
Published: (2025)

Offline Reinforcement Learning for Learning to Dispatch for Job Shop Scheduling
by: van Remmerden, Jesse, et al.
Published: (2024)

Generalizing Beyond Suboptimality: Offline Reinforcement Learning Learns Effective Scheduling through Random Data
by: van Remmerden, Jesse, et al.
Published: (2025)

Graph Neural Networks for Job Shop Scheduling Problems: A Survey
by: Smit, Igor G., et al.
Published: (2024)

Deep Multi-Objective Reinforcement Learning for Utility-Based Infrastructural Maintenance Optimization
by: van Remmerden, Jesse, et al.
Published: (2024)

Unsupervised anomaly detection algorithms on real-world data: how many do we need?
by: Bouman, Roel, et al.
Published: (2023)

Probing Neural Combinatorial Optimization Models
by: Zhang, Zhiqin, et al.
Published: (2025)

Learning Efficient and Fair Policies for Uncertainty-Aware Collaborative Human-Robot Order Picking
by: Smit, Igor G., et al.
Published: (2024)

A Rollout-Based Algorithm and Reward Function for Resource Allocation in Business Processes
by: Middelhuis, Jeroen, et al.
Published: (2025)

Maintenance Strategies for Sewer Pipes with Multi-State Degradation and Deep Reinforcement Learning
by: Jimenez-Roa, Lisandro A., et al.
Published: (2024)

Reinforcement Learning Methods for Neighborhood Selection in Local Search
by: Molinghen, Yannick, et al.
Published: (2026)

Adaptive Neighborhood-Constrained Q Learning for Offline Reinforcement Learning
by: Mao, Yixiu, et al.
Published: (2025)

ParBalans: Parallel Multi-Armed Bandits-based Adaptive Large Neighborhood Search
by: Yilmaz, Alican, et al.
Published: (2025)

Scheduling That Speaks: An Interpretable Programmatic Reinforcement Learning Framework
by: Hu, Chengpeng, et al.
Published: (2026)

Automated Reinforcement Learning: An Overview
by: Afshar, Reza Refaei, et al.
Published: (2022)

Adaptive Replay Buffer for Offline-to-Online Reinforcement Learning
by: Song, Chihyeon, et al.
Published: (2025)

Controllable Flow Matching for Online Reinforcement Learning
by: Wang, Bin, et al.
Published: (2025)

Adaptive Data Exploitation in Deep Reinforcement Learning
by: Yuan, Mingqi, et al.
Published: (2025)

Balans: Multi-Armed Bandits-based Adaptive Large Neighborhood Search for Mixed-Integer Programming Problem
by: Cai, Junyang, et al.
Published: (2024)

HALO: Hierarchical Reinforcement Learning for Large-Scale Adaptive Traffic Signal Control
by: Zhu, Yaqiao, et al.
Published: (2025)

Understanding the Nature of Depth-1 Equivariant Quantum Circuit
by: Teo, Jonathan, et al.
Published: (2025)

DiPRL: Learning Discrete Programmatic Policies via Architecture Entropy Regularization
by: Hu, Chengpeng, et al.
Published: (2026)

Deep Reinforcement Learning with Task-Adaptive Retrieval via Hypernetwork
by: Jin, Yonggang, et al.
Published: (2023)

Bayesian Deep Learning Via Expectation Maximization and Turbo Deep Approximate Message Passing
by: Xu, Wei, et al.
Published: (2024)

Online Training and Pruning of Deep Reinforcement Learning Networks
by: Guenter, Valentin Frank Ingmar, et al.
Published: (2025)

Adaptive Policy Selection and Fine-Tuning under Interaction Budgets for Offline-to-Online Reinforcement Learning
by: Bozkurt, Alper Kamil, et al.
Published: (2026)

Multi-Scale Adaptive Neighborhood Awareness Transformer For Graph Fraud Detection
by: Lv, Jiaqi, et al.
Published: (2026)

Adaptive Guidance Accelerates Reinforcement Learning of Reasoning Models
by: Nath, Vaskar, et al.
Published: (2025)

Adaptive $Q$-Network: On-the-fly Target Selection for Deep Reinforcement Learning
by: Vincent, Théo, et al.
Published: (2024)

Robust Deep Reinforcement Learning with Adaptive Adversarial Perturbations in Action Space
by: Liu, Qianmei, et al.
Published: (2024)

Adaptive Multi-Agent Deep Reinforcement Learning for Timely Healthcare Interventions
by: Shaik, Thanveer, et al.
Published: (2023)

Bayes Adaptive Monte Carlo Tree Search for Offline Model-based Reinforcement Learning
by: Chen, Jiayu, et al.
Published: (2024)

Online Preference-based Reinforcement Learning with Self-augmented Feedback from Large Language Model
by: Tu, Songjun, et al.
Published: (2024)

OffSeeker: Online Reinforcement Learning Is Not All You Need for Deep Research Agents
by: Zhou, Yuhang, et al.
Published: (2026)

Learning with Foresight: Enhancing Neural Routing Policy via Multi-Node Lookahead Prediction
by: Jiang, Xia, et al.
Published: (2026)

Towards Batch-to-Streaming Deep Reinforcement Learning for Continuous Control
by: De Monte, Riccardo, et al.
Published: (2026)

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

ROAD: Adaptive Data Mixing for Offline-to-Online Reinforcement Learning via Bi-Level Optimization
by: Yang, Letian, et al.
Published: (2026)

Adaptive Rollout Allocation for Online Reinforcement Learning with Verifiable Rewards
by: Nguyen, Hieu Trung, et al.
Published: (2026)