Notes:
GitHub: Diet in PuLP.
We run optimization model cases 10 times faster, fully using the parallel capabilities of the CPU cores/threads in a modern computer.
We compare a linear programming model written using Julia/JuMP with the same model written using Python/Pyomo.
This series of 13 articles compares Python libraries Pyomo, PuLP, OR-Tools, Gekko, CVXPY, and SciPy for building a linear programming model.
We've collated links to dozens of websites about optimization modelling. The links are organized into several categories.
The selection of a better fantasy sports team can substantially improve performance. Excel plus OpenSolver can pick an optimal team.
We report our experience of Copilot coding a non-trivial optimization model, focussing on what went well and what didn't go well as the model evolves.
Job sequencing is a common problem. Excel Solver can help you make optimal job sequencing decisions to minimize cost.
Sometimes we need more power to solve a model. This article describes how to solve a model using the CPLEX solver via the NEOS Server.
Using the SciPy library, we find an optimal solution to Aryabhata's approximation of trigonometric functions using ratios of quadratic polynomials.
We present an example of project crashing using an optimization model to help the project manager decide what to do.
This series explores optimization of a "picking warehouse" by improving the warehouse design and efficiency of the picking process.
We describe an example of how to represent price breaks in a linear programming model, built in Excel using Solver or OpenSolver.
