Image de couverture de livre

Learning Memory-Enhanced Improvement Heuristics for Flexible Job Shop Scheduling

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Wang, Jiaqi, Cao, Zhiguang, Zhao, Peng, Cao, Rui, Xiao, Yubin, Jiang, Yuan, Zhou, You
Format:	Preprint
Publié:	2026
Sujets:	Machine Learning Artificial Intelligence
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Deep Reinforcement Learning Guided Improvement Heuristic for Job Shop Scheduling
par: Zhang, Cong, et autres
Publié: (2022)

RESCHED: Rethinking Flexible Job Shop Scheduling from a Transformer-based Architecture with Simplified States
par: Xiao, Xiangjie, et autres
Publié: (2026)

Learning Topological Representations with Bidirectional Graph Attention Network for Solving Job Shop Scheduling Problem
par: Zhang, Cong, et autres
Publié: (2024)

Low-Cost Labels, Reliable Choices: Rollout-Calibrated Hyper-Heuristics for Job Shop Scheduling
par: Wei, Junhao, et autres
Publié: (2026)

Self-Evaluation for Job-Shop Scheduling
par: Echeverria, Imanol, et autres
Publié: (2025)

Variational Approach for Job Shop Scheduling
par: Oh, Seung Heon, et autres
Publié: (2026)

Learning to Solve Job Shop Scheduling under Uncertainty
par: Infantes, Guillaume, et autres
Publié: (2024)

Offline Reinforcement Learning for Learning to Dispatch for Job Shop Scheduling
par: van Remmerden, Jesse, et autres
Publié: (2024)

Neural Combinatorial Optimization for Stochastic Flexible Job Shop Scheduling Problems
par: Smit, Igor G., et autres
Publié: (2024)

Graph-RHO: Critical-path-aware Heterogeneous Graph Network for Long-Horizon Flexible Job-Shop Scheduling
par: Li, Yujie, et autres
Publié: (2026)

Learning-Guided Rolling Horizon Optimization for Long-Horizon Flexible Job-Shop Scheduling
par: Li, Sirui, et autres
Publié: (2025)

Decision Transformer for Enhancing Neural Local Search on the Job Shop Scheduling Problem
par: de Puiseau, Constantin Waubert, et autres
Publié: (2024)

Starjob: Dataset for LLM-Driven Job Shop Scheduling
par: Abgaryan, Henrik, et autres
Publié: (2025)

Graph Neural Networks for Job Shop Scheduling Problems: A Survey
par: Smit, Igor G., et autres
Publié: (2024)

Job Shop Scheduling Benchmark: Environments and Instances for Learning and Non-learning Methods
par: Reijnen, Robbert, et autres
Publié: (2023)

ReflecSched: Solving Dynamic Flexible Job-Shop Scheduling via LLM-Powered Hierarchical Reflection
par: Cao, Shijie, et autres
Publié: (2025)

Generalizable Heuristic Generation Through LLMs with Meta-Optimization
par: Shi, Yiding, et autres
Publié: (2025)

HGT-Scheduler: Deep Reinforcement Learning for the Job Shop Scheduling Problem via Heterogeneous Graph Transformers
par: Soykan, Bulent
Publié: (2026)

Beyond Training: Optimizing Reinforcement Learning Based Job Shop Scheduling Through Adaptive Action Sampling
par: de Puiseau, Constantin Waubert, et autres
Publié: (2024)

Self-Labeling the Job Shop Scheduling Problem
par: Corsini, Andrea, et autres
Publié: (2024)

Mamba Meets Scheduling: Learning to Solve Flexible Job Shop Scheduling with Efficient Sequence Modeling
par: Cao, Zhi, et autres
Publié: (2026)

Learning-enabled Flexible Job-shop Scheduling for Scalable Smart Manufacturing
par: Moon, Sihoon, et autres
Publié: (2024)

Optimizing Job Shop Scheduling in the Furniture Industry: A Reinforcement Learning Approach Considering Machine Setup, Batch Variability, and Intralogistics
par: Schneevogt, Malte, et autres
Publié: (2024)

RADAR: Learning to Route with Asymmetry-aware DistAnce Representations
par: Yi, Hang, et autres
Publié: (2026)

Rethinking Light Decoder-based Solvers for Vehicle Routing Problems
par: Huang, Ziwei, et autres
Publié: (2025)

Deep Reinforcement Learning for Flexible Job Shop Scheduling with Random Job Arrivals
par: Tang, Yu, et autres
Publié: (2026)

Learning to Optimize Job Shop Scheduling Under Structural Uncertainty
par: Zhang, Rui, et autres
Publié: (2026)

ReLA: Representation Learning and Aggregation for Job Scheduling with Reinforcement Learning
par: Kwan, Zhengyi, et autres
Publié: (2026)

Hierarchical Learning-based Graph Partition for Large-scale Vehicle Routing Problems
par: Pan, Yuxin, et autres
Publié: (2025)

HRLAIF: Improvements in Helpfulness and Harmlessness in Open-domain Reinforcement Learning From AI Feedback
par: Li, Ang, et autres
Publié: (2024)

Learning to Handle Complex Constraints for Vehicle Routing Problems
par: Bi, Jieyi, et autres
Publié: (2024)

Going Beyond Heuristics by Imposing Policy Improvement as a Constraint
par: Lee, Chi-Chang, et autres
Publié: (2025)

Adversarial Generative Flow Network for Solving Vehicle Routing Problems
par: Zhang, Ni, et autres
Publié: (2025)

VAGPO: Vision-augmented Asymmetric Group Preference Optimization for Graph Routing Problems
par: Liu, Shiyan, et autres
Publié: (2025)

Learning Scenario Reduction for Two-Stage Robust Optimization with Discrete Uncertainty
par: Lin, Tianjue, et autres
Publié: (2026)

Diversity Optimization for Travelling Salesman Problem via Deep Reinforcement Learning
par: Li, Qi, et autres
Publié: (2025)

Shopping MMLU: A Massive Multi-Task Online Shopping Benchmark for Large Language Models
par: Jin, Yilun, et autres
Publié: (2024)

Scaling Combinatorial Optimization Neural Improvement Heuristics with Online Search and Adaptation
par: Verdù, Federico Julian Camerota, et autres
Publié: (2024)

GraphCare: Enhancing Healthcare Predictions with Personalized Knowledge Graphs
par: Jiang, Pengcheng, et autres
Publié: (2023)

Probing Neural Combinatorial Optimization Models
par: Zhang, Zhiqin, et autres
Publié: (2025)