On the public citation graph

Deep Reinforcement Learning for Optimizing Agri-Food Supply Chain

https://doi.org/10.2139/ssrn.4868017
0 signed · 58 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

Is this your work? Sign in with ORCID and put your name on the claims that are yours.
Claim with ORCID
Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.
See reference health

What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/s10668-023-02992-wopenalex-snapshot
Mathematical modeling for sustainable agri-food supply chain
inferredcites →https://doi.org/10.1016/j.biosystemseng.2013.10.014openalex-snapshot
Agrifood supply chain management: A comprehensive hierarchical decision-making framework and a critical taxonomy
inferredcites →https://doi.org/10.1016/j.cie.2018.03.039openalex-snapshot
Real-time scheduling for a smart factory using a reinforcement learning approach
inferredcites →https://doi.org/10.1016/j.cirpj.2022.11.003openalex-snapshot
Deep reinforcement learning in smart manufacturing: A review and prospects
inferredcites →https://doi.org/10.1016/j.compind.2020.103188openalex-snapshot
Special issue on Agri-Food 4.0 and digitalization in agriculture supply chains - New directions, challenges and applications
inferredcites →https://doi.org/10.1016/j.dche.2022.100073openalex-snapshot
Distributional reinforcement learning for inventory management in multi-echelon supply chains
inferredcites →https://doi.org/10.1016/j.ejor.2008.02.014openalex-snapshot
Application of planning models in the agri-food supply chain: A review
inferredcites →https://doi.org/10.1016/j.ejor.2021.07.016openalex-snapshot
Deep reinforcement learning for inventory control: A roadmap
inferredcites →https://doi.org/10.1016/j.engappai.2023.107403openalex-snapshot
An application of deep reinforcement learning and vendor-managed inventory in perishable supply chain management
inferredcites →https://doi.org/10.1016/j.eswa.2017.08.046openalex-snapshot
Reinforcement learning approaches for specifying ordering policies of perishable inventory systems
inferredcites →https://doi.org/10.1016/j.ijpe.2010.08.002openalex-snapshot
An inventory system with single distributor and multiple retailers: Operating scenarios and performance comparison
inferredcites →https://doi.org/10.1016/j.ijpe.2014.09.023openalex-snapshot
Agricultural supply chain optimization and complexity: A comparison of analytic vs simulated solutions and policies
inferredcites →https://doi.org/10.1016/j.ijpe.2015.02.013openalex-snapshot
Pricing and inventory management in the presence of strategic customers with risk preference and decreasing value
inferredcites →https://doi.org/10.1016/j.ijpe.2020.107972openalex-snapshot
Can supply chain risk management practices mitigate the disruption impacts on supply chains’ resilience and robustness? Evidence from an empirical survey in a COVID-19 outbreak era
inferredcites →https://doi.org/10.1016/j.ijpe.2021.108075openalex-snapshot
Impact of COVID-19 outbreak on employee performance – Moderating role of industry 4.0 base technologies
inferredcites →https://doi.org/10.1016/j.ijpe.2021.108250openalex-snapshot
Artificial intelligence applications in supply chain management
inferredcites →https://doi.org/10.1016/j.ijpe.2021.108367openalex-snapshot
Optimal pricing strategy: How to sell to strategic consumers?
inferredcites →https://doi.org/10.1016/j.ijpe.2023.109088openalex-snapshot
Deep Reinforcement Learning for One-Warehouse Multi-Retailer inventory management
inferredcites →https://doi.org/10.1016/j.ijpe.2023.109133openalex-snapshot
Deep reinforcement learning for demand fulfillment in online retail
inferredcites →https://doi.org/10.1016/j.ijpe.2024.109154openalex-snapshot
A deep Q-learning approach to optimize ordering and dynamic pricing decisions in the presence of strategic customers
inferredcites →https://doi.org/10.1016/j.simpat.2015.07.004openalex-snapshot
A reinforcement learning methodology for a human resource planning problem considering knowledge-based promotion
inferredcites →https://doi.org/10.1016/j.spc.2024.01.016openalex-snapshot
Virtual agri-food supply chains: A holistic digital twin for sustainable food ecosystem design, control and transparency
inferredcites →https://doi.org/10.1016/j.tre.2022.102712openalex-snapshot
Reinforcement learning for logistics and supply chain management: Methodologies, state of the art, and future opportunities
inferredcites →https://doi.org/10.1038/nature14236openalex-snapshot
Human-level control through deep reinforcement learning
inferredcites →https://doi.org/10.1080/00207540110118640openalex-snapshot
Global supply chain management: A reinforcement learning approach
inferredcites →https://doi.org/10.1080/00207543.2018.1447706openalex-snapshot
Conceptual framework for designing agri-food supply chains under uncertainty by mathematical programming models
inferredcites →https://doi.org/10.1080/00207543.2020.1870013openalex-snapshot
Learning to schedule job-shop problems: representation and policy learning using graph neural network and reinforcement learning
inferredcites →https://doi.org/10.1080/00207543.2021.1972179openalex-snapshot
Explainable reinforcement learning in production control of job shop manufacturing system
inferredcites →https://doi.org/10.1080/00207543.2021.1973138openalex-snapshot
Deep reinforcement learning in production systems: a systematic literature review
inferredcites →https://doi.org/10.1080/00207543.2022.2140221openalex-snapshot
A review on reinforcement learning algorithms and applications in supply chain management
inferredcites →https://doi.org/10.1080/23302674.2019.1600766openalex-snapshot
Inventory control for nonperishable and perishable goods based on model predictive control
inferredcites →https://doi.org/10.1108/bfj-06-2022-0490openalex-snapshot
Technological innovation in agri-food supply chains
inferredcites →https://doi.org/10.1109/access.2018.2870856openalex-snapshot
Simulation-Based Optimization on Control Strategies of Three-Echelon Inventory in Hybrid Supply Chain With Order Uncertainty
inferredcites →https://doi.org/10.1109/access.2019.2956287openalex-snapshot
New Optimal-Control-Based Advertising Strategies and Coordination of a Supply Chain With Differentiated Products Under Consignment Contract
inferredcites →https://doi.org/10.1109/access.2021.3062410openalex-snapshot
Effective Management for Blockchain-Based Agri-Food Supply Chains Using Deep Reinforcement Learning
inferredcites →https://doi.org/10.1109/access.2022.3205720openalex-snapshot
Optimization of Apparel Supply Chain Using Deep Reinforcement Learning
inferredcites →https://doi.org/10.1109/es.2017.16openalex-snapshot
The Supply Chain Network on Cloud Manufacturing Environment Based on COIN Model with Q-Learning Algorithm
inferredcites →https://doi.org/10.1109/ic_aset49463.2020.9318258openalex-snapshot
A Policy Gradient Based Reinforcement Learning Method for Supply Chain Management
inferredcites →https://doi.org/10.1109/tccn.2019.2952909openalex-snapshot
A Deep Actor-Critic Reinforcement Learning Framework for Dynamic Multichannel Access
inferredcites →https://doi.org/10.1109/tnet.2020.3037231openalex-snapshot
An Actor-Critic-Based Transfer Learning Framework for Experience-Driven Networking
inferredcites →https://doi.org/10.1109/tnn.2004.842673openalex-snapshot
Reinforcement Learning: An Introduction
inferredcites →https://doi.org/10.1109/tsmcc.2012.2218595openalex-snapshot
A Survey of Actor-Critic Reinforcement Learning: Standard and Natural Policy Gradients
inferredcites →https://doi.org/10.1145/3477600openalex-snapshot
Reinforcement Learning in Healthcare: A Survey
inferredcites →https://doi.org/10.1287/educ.2022.0246openalex-snapshot
Supply Chain Resilience: Impact of Stakeholder Behavior and Trustworthy Information Sharing with a Case Study on Pharmaceutical Supply Chains
inferredcites →https://doi.org/10.1287/msom.2020.0939openalex-snapshot
A Deep Q-Network for the Beer Game: Deep Reinforcement Learning for Inventory Optimization
inferredcites →https://doi.org/10.1287/msom.2021.1010openalex-snapshot
Artificial Shortage in Agricultural Supply Chains
inferredcites →https://doi.org/10.1287/msom.2021.1064openalex-snapshot
Can Deep Reinforcement Learning Improve Inventory Management? Performance on Lost Sales, Dual-Sourcing, and Multi-Echelon Problems
inferredcites →https://doi.org/10.1287/opre.2021.0694openalex-snapshot
Inventory Control and Learning for One-Warehouse Multistore System with Censored Demand
inferredcites →https://doi.org/10.1287/opre.2021.2251openalex-snapshot
Conveying Demand Information in Serial Supply Chains with Capacity Limits
inferredcites →https://doi.org/10.1287/trsc.2022.0042openalex-snapshot
Dynamic Courier Capacity Acquisition in Rapid Delivery Systems: A Deep Q-Learning Approach
inferredcites →https://doi.org/10.1609/aaai.v30i1.10295openalex-snapshot
Deep Reinforcement Learning with Double Q-Learning
inferredcites →https://doi.org/10.23919/csms.2021.0027openalex-snapshot
A Review of Reinforcement Learning Based Intelligent Optimization for Manufacturing Scheduling
inferredcites →https://doi.org/10.3390/a14080240openalex-snapshot
Adaptive Supply Chain: Demand–Supply Synchronization Using Deep Reinforcement Learning
inferredcites →https://doi.org/10.3390/foods13010150openalex-snapshot
A Conceptual Model Relationship between Industry 4.0—Food-Agriculture Nexus and Agroecosystem: A Literature Review and Knowledge Gaps
inferredcites →https://doi.org/10.3390/su12124877openalex-snapshot
A Multi-Item Replenishment Problem with Carbon Cap-and-Trade under Uncertainty
inferredcites →https://doi.org/10.3934/agrfood.2019.1.1openalex-snapshot
A heuristic for the selection of appropriate diagnostic tools in large-scale sugarcane supply systems
inferredcites →https://doi.org/10.4236/iim.2017.92004openalex-snapshot
Agri-food Supply Chain Management: Literature Review
inferredcites →https://doi.org/10.48550/arxiv.2010.12367openalex-snapshot
Learning to Dispatch for Job Shop Scheduling via Deep Reinforcement Learning
Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.