demand forecasting

DataFunSummit

Dec 31, 2023 · Artificial Intelligence

Intelligent Supply Chain Transformation: From Zero to One and Beyond – Concepts, Technologies, and Case Studies

The article examines how cutting‑edge technologies such as machine learning and operations research can reshape consumer‑retail supply chains, outlining a four‑part framework that covers company background, the evolution from basic to intelligent supply chains, acceleration strategies, and real‑world best‑practice case studies.

AIOptimizationcase study

0 likes · 20 min read

Intelligent Supply Chain Transformation: From Zero to One and Beyond – Concepts, Technologies, and Case Studies

Model Perspective

Oct 25, 2023 · Operations

How Math Models Can Turn Your Coffee Shop into a Profit Machine

This article shows how forecasting, linear programming, EOQ inventory, pricing elasticity, and location‑selection models can be applied to a coffee shop to predict foot traffic, optimize menus, reduce waste, set optimal prices, and choose the best site, ultimately boosting profitability.

Linear Programmingdemand forecastinginventory management

0 likes · 11 min read

How Math Models Can Turn Your Coffee Shop into a Profit Machine

DataFunTalk

Jul 31, 2023 · Operations

Applying Causal Inference to Inventory Management: Demand Forecasting and Strategy Implementation

This article explores how causal inference techniques, including dynamic Bayesian networks and time‑series models, can be used to improve demand forecasting and replenishment strategies in inventory management, offering both theoretical concepts and practical case studies for operational decision‑making.

causal inferencedemand forecastingdynamic Bayesian network

0 likes · 14 min read

Applying Causal Inference to Inventory Management: Demand Forecasting and Strategy Implementation

DataFunTalk

Feb 13, 2023 · Operations

Supply Chain Algorithms and Fresh Food Automatic Replenishment System at Hema

This article presents a comprehensive overview of Hema's supply chain, detailing its business model, logistics‑inventory trade‑offs, algorithmic positioning, and the design, modules, and achievements of its fresh‑food automatic replenishment system, which leverages demand forecasting, graph neural networks, and dynamic inventory control.

Artificial IntelligenceFresh Food ReplenishmentGraph Neural Networks

0 likes · 11 min read

Supply Chain Algorithms and Fresh Food Automatic Replenishment System at Hema

NetEase Yanxuan Technology Product Team

Apr 18, 2022 · Artificial Intelligence

Supply‑Demand Coordination in E‑commerce: Challenges and Algorithmic Solutions

Effective e‑commerce supply‑demand coordination requires accurate SKU‑level forecasting, optimized replenishment under MOQ and lead‑time constraints, and dynamic post‑sale traffic control, using a blend of time‑series, tree‑based and deep learning models together with expert knowledge to minimize inventory costs and avoid stock‑outs.

AIAlgorithmOptimization

0 likes · 10 min read

Supply‑Demand Coordination in E‑commerce: Challenges and Algorithmic Solutions

Didi Tech

Jun 4, 2021 · Artificial Intelligence

Graph Convolutional Network for Shared Bike Demand Forecasting: Time Series Modeling and Multi‑Task Learning

The paper presents a graph convolutional network approach that leverages multi‑task learning and spectral graph convolutions to forecast shared‑bike inflow, outflow, and demand gaps across a city’s non‑Euclidean parking network, demonstrating improved accuracy over traditional time‑series baselines while noting scalability and directional graph limitations.

GCNdemand forecastinggraph neural network

0 likes · 13 min read

Graph Convolutional Network for Shared Bike Demand Forecasting: Time Series Modeling and Multi‑Task Learning

JD Retail Technology

Nov 8, 2019 · Operations

Smart Supply Chain Operations for JD.com 11.11 Promotion: Integrated Planning, AI‑Driven Forecasting, and Real‑Time Optimization

JD.com's Smart Supply Chain Y Business Management team collaborated across divisions to implement AI‑driven demand forecasting, automated replenishment, micro‑service architecture, and real‑time monitoring, enabling precise inventory control, cost reduction, and seamless 11.11 promotion fulfillment through integrated planning, pricing, and fulfillment innovations.

AIdemand forecastinge‑commerce

0 likes · 21 min read

Smart Supply Chain Operations for JD.com 11.11 Promotion: Integrated Planning, AI‑Driven Forecasting, and Real‑Time Optimization

DataFunTalk

Mar 12, 2019 · Artificial Intelligence

Demand Forecasting Practices in Alibaba Retail: From Mean Models to Deep Learning

This article outlines Alibaba Retail's demand forecasting workflow, describing the evolution from simple mean and time‑series models to machine‑learning and deep‑learning approaches, the incorporation of feature engineering, operational plans, and methods for estimating prediction uncertainty to support intelligent replenishment.

AIDeep LearningInventory

0 likes · 13 min read

Demand Forecasting Practices in Alibaba Retail: From Mean Models to Deep Learning