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We explore two aspects of refactoring an existing optimization model: Modularization and adding model variations.
Why does my model find different solutions? Some solutions are better than others – how can that be true? How do I find the overall best solution?
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?
Given available resources, what mix of products will maximize profit? We can answer to question using Excel and the Solver add-in.
We minimize the number of racks required to accommodate all pallets in a warehouse, freeing space for other activities and allowing company growth.
We've collated many interesting optimization models in our GitHub repository. The focus is on Excel and Python models.
We minimize trim waste in a paper manufacturing process. A theoretically perfect solution is impractical, so what can we do?
Designing an optimization model is difficult. This article explains common mathematical notation used to define optimization model formulations.
