Workshop on AI
for Supply Chain:
Today and Future
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Coordinated Communication and Inventory Optimization in Multi-Retailer Supply Chains
Speeding up $KNN−\overline{W}H$ for Origin–Destination Travel Time Estimation
Measuring Time Series Forecast Stability for Demand Planning
Shifu: A Self-Learning Framework for Automating Root Cause Analysis in Logistics Operations (oral)
Hierarchical Reinforcement Learning for Real-Time Policy Optimization in Complex Logistics Networks
Confidence Scoring for LLM-Generated SQL in Supply Chain Data Extraction
TAT: Temporal-Aligned Transformer for Multi-Horizon Peak Demand Forecasting
C‑MAG: Cascade Multimodal Attributed Graphs for Supply Chain Link Prediction
Visualising Industry Network-based Supply Chain Risks for Informed Opportunity Management
RSight: A deep neural network for product demand forecasting over geographic regions
Beyond Mere Automation: A Techno-functional Framework for Gen AI in Supply Chain Operations
An end-to-end Causal Modeling Framework for Advanced Attribution in Supply Chain Operations
Foundation Models for Demand Forecasting via Dual-Strategy Ensembling
Interpretable Feature Selection for Truck Collision Injury Severity: A SHAP-RFE Approach
Challenges in Achieving Explainability & Control with Supply Chain Forecasts
LOGEX: Cost-Sensitive Bayesian Experimentation for Adaptive Decision-Making in Supply Chains
Intelligent Routing for Sparse Demand Forecasting: A Comparative Evaluation of Selection Strategies
Global-Decision-Focused Neural ODEs for Proactive Generator Deployment and Power Grid Resilience
Goldilocks: An Active Sampling Bandit That’s Just Right for Multi-Task Forecasting
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