Why does my model find different solutions? Some solutions are better than others – how can that be? How do I find the best solution?

We've collated many interesting optimization models in our GitHub repository. The focus is on Excel and Python models.

Designing an optimization model is difficult. This article explains common mathematical notation used to define optimization model formulations.

Given available stock of wire and a list of pieces required, what is the best way to cut the stock to fulfil demand while minimizing waste?

Bin packing is a common problem. A new formulation helps us solve a simple, yet difficult to solve, bin packing model.

Using the SciPy library, we find an optimal solution to Aryabhata's approximation of trigonometric functions using ratios of quadratic polynomials.

We run optimization model cases 10 times faster, fully using the parallel capabilities of the CPU cores/threads in a modern computer.

Formulating logic conditions in linear programs can be difficult. This two-part article series explains how, using easy to follow steps.

Given available resources, what mix of products will maximize profit? We can answer to question using Excel and the Solver add-in.

Minimize the number of racks to store all pallets in a warehouse, freeing space for other activities and allowing company growth.

How many other optimal solutions exist? How do I find those solutions. This article explains how to use the CPLEX solution pool.

This article series implements a staff scheduling model in Excel using OpenSolver, then in Python using Pyomo.