The selection of a better fantasy sports team can substantially improve performance. Excel plus OpenSolver can pick an optimal team.

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

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

We describe an example of how to represent price breaks in a linear programming model, built in Excel using Solver or OpenSolver.

To compare optimization modelling in Excel and Python, we replicate a Python model then compare it with an equivalent Excel implementation.

We compare a linear programming model written using Julia/JuMP with the same model written using Python/Pyomo.

Optimal facility location is a common & difficult decision that organizations need to make. We build a location optimization model in Excel.

Academic research papers can be tremendously valuable. But only if they are complete. So, academics, please publish your data and code.

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

Allocating people to teams is a task common in both sport and business. We allocate 32 people to 4 teams that are as balanced as possible.

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

We explore methods to decide the best order for positioning devices in a rack: enumerate, heuristic, constraint programming, and linear program.