Copertina

Reinforcement Learning for Multi-Objective Multi-Echelon Supply Chain Optimisation

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Rachman, Rifny, Tingey, Josh, Allmendinger, Richard, Shukla, Pradyumn, Pan, Wei
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Artificial Intelligence
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

MIRACL: A Diverse Meta-Reinforcement Learning for Multi-Objective Multi-Echelon Combinatorial Supply Chain Optimisation
di: Rachman, Rifny, et al.
Pubblicazione: (2026)

MORSE: Multi-Objective Reinforcement Learning via Strategy Evolution for Supply Chain Optimization
di: Kotecha, Niki, et al.
Pubblicazione: (2025)

Comparing Deep Reinforcement Learning Algorithms in Two-Echelon Supply Chains
di: Stranieri, Francesco, et al.
Pubblicazione: (2022)

Multi-Objective Deep Reinforcement Learning for Optimisation in Autonomous Systems
di: Rosero, Juan C., et al.
Pubblicazione: (2024)

Dynamic Detection of Relevant Objectives and Adaptation to Preference Drifts in Interactive Evolutionary Multi-Objective Optimization
di: Shavarani, Seyed Mahdi, et al.
Pubblicazione: (2024)

Beyond Accuracy: Evaluating Forecasting Models by Multi-Echelon Inventory Cost
di: Marik, Swata, et al.
Pubblicazione: (2026)

Where are the Humans? A Scoping Review of Fairness in Multi-agent AI Systems
di: Allmendinger, Simeon, et al.
Pubblicazione: (2026)

Multi-Objective Reinforcement Learning for Water Management
di: Osika, Zuzanna, et al.
Pubblicazione: (2025)

Demonstration Guided Multi-Objective Reinforcement Learning
di: Lu, Junlin, et al.
Pubblicazione: (2024)

Interpretability by Design for Efficient Multi-Objective Reinforcement Learning
di: Xia, Qiyue, et al.
Pubblicazione: (2025)

TREX: Trajectory Explanations for Multi-Objective Reinforcement Learning
di: Rajapakse, Dilina, et al.
Pubblicazione: (2026)

STEMO: Early Spatio-temporal Forecasting with Multi-Objective Reinforcement Learning
di: Shao, Wei, et al.
Pubblicazione: (2024)

An Offline Adaptation Framework for Constrained Multi-Objective Reinforcement Learning
di: Lin, Qian, et al.
Pubblicazione: (2024)

In Search for Architectures and Loss Functions in Multi-Objective Reinforcement Learning
di: Terekhov, Mikhail, et al.
Pubblicazione: (2024)

Normative Common Ground Replication (NormCoRe): Replication-by-Translation for Studying Norms in Multi-Agent AI
di: Deck, Luca, et al.
Pubblicazione: (2026)

Adaptive Alignment: Dynamic Preference Adjustments via Multi-Objective Reinforcement Learning for Pluralistic AI
di: Harland, Hadassah, et al.
Pubblicazione: (2024)

Self-Compression of Chain-of-Thought via Multi-Agent Reinforcement Learning
di: Chen, Yiqun, et al.
Pubblicazione: (2026)

DRAFT-RL: Multi-Agent Chain-of-Draft Reasoning for Reinforcement Learning-Enhanced LLMs
di: Li, Yuanhao, et al.
Pubblicazione: (2025)

Agentic LLMs in the Supply Chain: Towards Autonomous Multi-Agent Consensus-Seeking
di: Jannelli, Valeria, et al.
Pubblicazione: (2024)

FairDICE: Fairness-Driven Offline Multi-Objective Reinforcement Learning
di: Kim, Woosung, et al.
Pubblicazione: (2025)

Scalable Multi-Objective and Meta Reinforcement Learning via Gradient Estimation
di: Zhang, Zhenshuo, et al.
Pubblicazione: (2025)

Safe and Balanced: A Framework for Constrained Multi-Objective Reinforcement Learning
di: Gu, Shangding, et al.
Pubblicazione: (2024)

Navigating Trade-offs: Policy Summarization for Multi-Objective Reinforcement Learning
di: Osika, Zuzanna, et al.
Pubblicazione: (2024)

Combining Multi-Objective Bayesian Optimization with Reinforcement Learning for TinyML
di: Deutel, Mark, et al.
Pubblicazione: (2023)

Developing and Integrating Trust Modeling into Multi-Objective Reinforcement Learning for Intelligent Agricultural Management
di: Wang, Zhaoan, et al.
Pubblicazione: (2025)

REMOR: Automated Peer Review Generation with LLM Reasoning and Multi-Objective Reinforcement Learning
di: Taechoyotin, Pawin, et al.
Pubblicazione: (2025)

PROPEL: Supervised and Reinforcement Learning for Large-Scale Supply Chain Planning
di: Akhlaghi, Vahid Eghbal, et al.
Pubblicazione: (2025)

Multi-Objective Reinforcement Learning for Power Grid Topology Control
di: Lautenbacher, Thomas, et al.
Pubblicazione: (2025)

A Deep Q-Network Based on Radial Basis Functions for Multi-Echelon Inventory Management
di: Cheng, Liqiang, et al.
Pubblicazione: (2024)

Thinking Forward and Backward: Multi-Objective Reinforcement Learning for Retrieval-Augmented Reasoning
di: Wei, Wenda, et al.
Pubblicazione: (2025)

Optimizing Multi-Tier Supply Chain Ordering with LNN+XGBoost: Mitigating the Bullwhip Effect
di: Tong, Chunan
Pubblicazione: (2025)

Hybrid Action Based Reinforcement Learning for Multi-Objective Compatible Autonomous Driving
di: Jin, Guizhe, et al.
Pubblicazione: (2025)

A Meta-Learning Approach for Multi-Objective Reinforcement Learning in Sustainable Home Environments
di: Lu, Junlin, et al.
Pubblicazione: (2024)

Adaptive Inventory Strategies using Deep Reinforcement Learning for Dynamic Agri-Food Supply Chains
di: Kaur, Amandeep, et al.
Pubblicazione: (2025)

Reinforcement Learning for Autonomous Warehouse Orchestration in SAP Logistics Execution: Redefining Supply Chain Agility
di: Pillella, Sumanth
Pubblicazione: (2025)

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

Hindsight Preference Replay Improves Preference-Conditioned Multi-Objective Reinforcement Learning
di: Shianifar, Jonaid, et al.
Pubblicazione: (2026)

Multi-granularity Knowledge Transfer for Continual Reinforcement Learning
di: Pan, Chaofan, et al.
Pubblicazione: (2024)

Learning to Correct: Calibrated Reinforcement Learning for Multi-Attempt Chain-of-Thought
di: Ildiz, Muhammed Emrullah, et al.
Pubblicazione: (2026)

Towards Efficient Multi-Objective Optimisation for Real-World Power Grid Topology Control
di: Manyari, Yassine El, et al.
Pubblicazione: (2025)