inventory-optimization

Calculate EOQ, safety stock, and reorder points using inventory models.

56|16|Updated Oct 18, 2025

Search Tags:#optimization #forecasting #cost reduction #inventory #supply chain #stock management

Ready to run

npx skills add https://github.com/kishorkukreja/awesome-supply-chain --skill inventory-optimization

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: inventory-optimization
Source: https://github.com/kishorkukreja/awesome-supply-chain/tree/main/skills/inventory-optimization
Command: npx skills add https://github.com/kishorkukreja/awesome-supply-chain --skill inventory-optimization

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires numpy, scipy, pandas, statsmodels, simpy, ciw, pulp, pyomo, matplotlib, seaborn, plotly, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill helps businesses balance inventory costs with service levels, preventing stockouts while minimizing excess inventory and associated holding costs.

Core Features & Use Cases

Inventory Calculation: Determines optimal order quantities (EOQ), safety stock levels, and reorder points.
Policy Design: Supports continuous ((s, Q)) and periodic ((R, S)) review policies.
Segmentation: Implements ABC-XYZ analysis to tailor inventory strategies to item value and demand variability.
Use Case: A retail manager can use this Skill to calculate the ideal safety stock for a popular product to ensure it's available during peak season without overstocking.

Quick Start

Use the inventory-optimization skill to calculate the Economic Order Quantity for a product with annual demand of 10,000 units, an order cost of $100, and a holding cost rate of 25% on a unit cost of $50.

Frequently Asked Questions about inventory-optimization

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I calculate Economic Order Quantity and safety stock in Python?▼

To calculate Economic Order Quantity (EOQ) and safety stock in Python, you need the annual demand, order cost, and holding cost rate. This Skill uses numpy and scipy to compute optimal order quantities, safety stock levels, and reorder points.

What is the best way to optimize inventory levels for multi-SKU allocation within budget constraints?▼

The best way to optimize inventory levels for multi-SKU allocation within budget constraints is by applying ABC-XYZ analysis. This segments items by value and demand variability, allowing tailored inventory policies that balance cost-service trade-offs across diverse products.

How do you design continuous and periodic review policies for stock management?▼

Designing continuous and periodic review policies for stock management involves setting reorder points for (s, Q) policies and target levels for (R, S) policies. This Skill calculates these metrics to prevent stockouts while minimizing excess inventory holding costs.

Can I use pandas and statsmodels to address demand variability in supply chain forecasting?▼

Yes, you can use pandas and statsmodels to address demand variability in supply chain forecasting. This Skill leverages these dependencies to handle demand variability and lead times, calculating optimal inventory metrics and turnover rates.

Does this inventory optimization approach support cost reduction for retail peak season overstocking?▼

Yes, this inventory optimization approach supports cost reduction for retail peak season overstocking. It calculates optimal safety stock and reorder points to ensure product availability during demand spikes while actively minimizing excess inventory costs.