OptiChain: Simplifying Supply Chain Management
Project Information
- Category: Supply Chain
- Client: Data Dynamos
- Project Date: March 2023
- GitHub: OptiChain GitHub
Description
The Supply Chain Optimization is an advanced project focused on optimizing supply chain operations using reinforcement learning techniques. This project addresses key challenges in production management, demand forecasting, and profit maximization to ensure efficient supply chain management and improve overall profitability.
Key Features
- Production Management: Manages production schedules considering variable and fixed costs, and adjusts for distinct market requirements.
- Demand Forecasting: Uses ARIMA and LSTM models to predict future demand, aligning production with fluctuating demand over a 3-year period.
- Profit Optimization: Maximizes profits by balancing selling prices, production costs, and shipping expenses.
- Time Dimension: Adapts strategies dynamically within a 3-year timeframe as demand, costs, and other factors evolve.
Technical Highlights
- Implementation of reinforcement learning algorithms for decision-making in supply chain operations
- Integration of machine learning models (ARIMA, LSTM) for accurate demand forecasting
- Development of a dynamic optimization framework that adapts to changing market conditions
Impact
OptiChain demonstrates the potential of AI and machine learning in revolutionizing supply chain management. By providing data-driven insights and automated decision-making capabilities, it enables businesses to significantly improve their operational efficiency, reduce costs, and enhance their responsiveness to market changes.