This series of 13 articles compares Python libraries Pyomo, PuLP, OR-Tools, Gekko, CVXPY, and SciPy for building a linear programming model.
Page 19 of 35
We minimize trim waste in a paper manufacturing process. A theoretically perfect solution is impractical, so what can we do?
We describe an example of how to represent price breaks in a linear programming model, built in Excel using Solver or OpenSolver.
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?
Designing an optimization model is difficult. This article explains common mathematical notation used to define optimization model formulations.
Minimize the number of racks to store all pallets in a warehouse, freeing space for other activities and allowing company growth.
This article series implements a staff scheduling model in Excel using OpenSolver, then in Python using Pyomo.
A new role mining model is claimed to be more tractable and practical. We test that assertion using constraint programming and MILP.
Formulating logic conditions in linear programs can be difficult. This two-part article series explains how, using easy to follow steps.
Academic research papers can be tremendously valuable. But only if they are complete. So, academics, please publish your data and code.
The selection of a better fantasy sports team can substantially improve performance. Excel plus OpenSolver can pick an optimal team.
Using the SciPy library, we find an optimal solution to Aryabhata's approximation of trigonometric functions using ratios of quadratic polynomials.
Why does my model find different solutions? Some solutions are better than others – how can that be? How do I find the best solution?
