Optimal facility location is a common & difficult decision that organizations need to make. We build a location optimization model in Excel.
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We compare a linear programming model written using Julia/JuMP with the same model written using Python/Pyomo.
To compare optimization modelling in Excel and Python, we replicate a Python model then compare it with an equivalent Excel implementation.
This series of 13 articles compares Python libraries Pyomo, PuLP, OR-Tools, Gekko, CVXPY, and SciPy for building a linear programming model.
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 replicate a wood cutting pattern model from a published academic paper. Surprisingly, we find a better optimal solution.
We present an example of project crashing using an optimization model to help the project manager decide what to do.
The selection of a better fantasy sports team can substantially improve performance. Excel plus OpenSolver can pick an optimal team.
Formulating logic conditions in linear programs can be difficult. This two-part article series explains how, using easy to follow steps.
Using the SciPy library, we find an optimal solution to Aryabhata's approximation of trigonometric functions using ratios of quadratic polynomials.
We explore two aspects of refactoring an existing optimization model: Modularization and adding model variations.
This series explores optimization of a "picking warehouse" by improving the warehouse design and efficiency of the picking process.
