reinforcement-learning-supply-chain
CommunityOptimize supply chains with RL.
Data & Analytics#optimization#reinforcement learning#q-learning#supply chain#dynamic pricing#inventory control#dqn
Authorkishorkukreja
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This Skill enables the application of reinforcement learning techniques to solve complex, sequential decision-making problems within supply chain management, leading to optimized operational policies.
Core Features & Use Cases
- RL for Inventory: Learn optimal ordering policies to balance holding and backorder costs.
- Dynamic Pricing: Develop agents to adjust prices based on inventory, demand, and market conditions.
- Warehouse Automation: Control robot movements and task assignments for efficient operations.
- Sequential Optimization: Solve problems involving continuous decision-making under uncertainty.
Quick Start
Use the reinforcement-learning-supply-chain skill to train a Q-learning agent for inventory control with a mean demand of 10 and a maximum inventory of 50.
Dependency Matrix
Required Modules
numpytorch
Components
scriptsreferences
💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: reinforcement-learning-supply-chain Download link: https://github.com/kishorkukreja/awesome-supply-chain/archive/main.zip#reinforcement-learning-supply-chain Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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