A Gentle Introduction to Stochastic Programming

Mathematics A Gentle Introduction to Stochastic Programming How to make decisions when your spreadsheet is lying about the future Berend Markhorst Apr 30, 2026 15 min read Share Photo by Mathilda Khoo via Unsplash In my first TDS post, I wrote about how to translate a real-world problem into an integer linear program. In my second, I wrote about how to make that program robust against uncertainty. Both were variations on the same idea: take a fuzzy real-world question, squeeze it into an LP, and let a solver do the rest. There is a moment in every optimizer’s life, though, when the LP starts to feel a bit too neat. Demand is a number. Travel time is a number. Wind speed is a number. The model accepts the input, returns an optimal solution, and goes on its way.

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Excerpt limited to ~120 words for fair-use compliance. The full article is at Towards Data Science.