Use non-linear programming to find the optimal ordering policy that minimises capital, transportation and storage costs

Procurement management is a strategic approach to acquiring goods or services from preferred vendors within your defined budget, on or before a specific deadline.

Your goal is to balance supply and demand, so you maintain a minimum inventory level to meet your store's demand.

In this Article, we will present a simple methodology using Non-Linear Programming to design an optimal inventory replenishment strategy for a mid-size retail store, considering

• Transportation Costs from the Supplier Warehouse to the Store Reserve ($/Carton)
• Costs to finance your inventory (% of inventory value in $)
• Reserve (Store’s Warehouse) Rental Costs for storage ($/Carton)

As a Store Manager at a mid-sized retail location, you are responsible for setting replenishment quantities in the ERP.

For each SKU, when the inventory level falls below a defined threshold, your ERP system automatically issues a Purchase Order (PO) to your supplier.

You need to balance stock capacity, transportation costs, and inventory costs to determine the right quantity for your PO.

Which Quantity per replenishment (Qi) should you set in the ERP to minimise total costs?

In this repository, you will find all the code used to explain the concepts presented in the article.

• Procurement Strategy with Python.ipynb - Jupyter notebook with step-by-step analysis
• procurement_optimization.py - Standalone Python script

pip install -r requirements.txt
python procurement_optimization.py

• pandas
• pulp
• numpy
• scipy

Senior Supply Chain and Data Science consultant with international experience working on Logistics and Transportation operations.
For consulting or advising on analytics and sustainable supply chain transformation, feel free to contact me via Logigreen Consulting.
For more case studies, check my Personal Website.