inventory-routing-problem

Optimize inventory management and vehicle routing decisions using MIP solvers.

56|16|Updated Oct 18, 2025

Search Tags:#supply chain #route optimization #logistics optimization #inventory routing #VMI #delivery scheduling

Ready to run

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

💬 Prompt for ChatGPT / Claude Chat▼

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

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires numpy, pandas, pulp, scipy, matplotlib, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill solves the complex challenge of simultaneously optimizing inventory levels and vehicle routing decisions to minimize total system costs.

Core Features & Use Cases

Integrated Optimization: Jointly determines replenishment quantities and delivery schedules.
Cost Reduction: Minimizes holding costs, transportation expenses, and stockout penalties.
Use Case: A fuel distributor needs to schedule tanker truck deliveries to gas stations, ensuring stations don't run out of fuel while minimizing truck mileage and delivery costs.

Quick Start

Use the inventory-routing-problem skill to plan optimal deliveries for customers with current inventory and demand data.

Frequently Asked Questions about inventory-routing-problem

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

FAQPage Schema

How do I optimize inventory levels and vehicle routing simultaneously?▼

The Inventory Routing Problem (IRP) integrates inventory management and vehicle routing by jointly optimizing replenishment quantities and delivery schedules to minimize combined holding, transportation, and stockout costs.

What is the best way to schedule deliveries for vendor-managed inventory?▼

Scheduling vendor-managed inventory (VMI) deliveries requires integrated optimization models that jointly plan coordinated replenishment across deterministic or stochastic demand to minimize stockouts and transportation expenses.

Can I use Python and PuLP to model multi-period inventory routing problems?▼

Yes, Python libraries like PuLP, NumPy, and SciPy enable modeling and solving both single-period and multi-period Inventory Routing Problem variants using mixed-integer programming solvers.

Does this inventory routing approach support stochastic demand scenarios?▼

Yes, this inventory routing approach handles stochastic demand scenarios alongside deterministic demand, allowing you to balance holding costs and stockout penalties under demand uncertainty using MIP solvers.

How do I minimize transportation and holding costs for fuel distribution?▼

To minimize fuel distribution costs, apply integrated inventory-distribution planning to schedule tanker deliveries that prevent station stockouts while reducing truck mileage and delivery expenses.