Using the SciPy library, we find an optimal solution to Aryabhata's approximation of trigonometric functions using ratios of quadratic polynomials.
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We replicate a wood cutting pattern model from a published academic paper. Surprisingly, we find a better optimal solution.
Why does my model find different solutions? Some solutions are better than others – how can that be? How do I find the best solution?
Given available resources, what mix of products will maximize profit? We can answer to question using Excel and the Solver add-in.
This series explores optimization of a "picking warehouse" by improving the warehouse design and efficiency of the picking process.
Allocating people to teams is a task common in both sport and business. We allocate 32 people to 4 teams that are as balanced as possible.
Optimal facility location is a common & difficult decision that organizations need to make. We build a location optimization model in Excel.
We explore methods to decide the best order for positioning devices in a rack: enumerate, heuristic, constraint programming, and linear program.
The selection of a better fantasy sports team can substantially improve performance. Excel plus OpenSolver can pick an optimal team.
How many other optimal solutions exist? How do I find those solutions. This article explains how to use the CPLEX solution pool.
Job sequencing is a common problem. Excel Solver can help you make optimal job sequencing decisions to minimize cost.
Academic research papers can be tremendously valuable. But only if they are complete. So, academics, please publish your data and code.
This series of 13 articles compares Python libraries Pyomo, PuLP, OR-Tools, Gekko, CVXPY, and SciPy for building a linear programming model.
