13 votes
Accepted

My model has not finished evaluating in more than a day so can't test if it works, what is wrong with it?

Here a couple of changes/suggestions. Using a decimal dot for all constants forces most algorithms to switch from symbolic to numeric routines with machine floating point arithmetic; that's typically ...
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12 votes

Is there a faster way to solve this linear programming problem?

Your problem is not a linear programming problem, but rather a linear system of equations. You have 40 equations for 39 variables and so the problem is over-determined, but luckily it is still ...
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  • 35.7k
10 votes
Accepted

How can I quickly find the coordinates of key points?

Here the problem was solved with a different perspective. You may find other solutions but what made this interesting to me was transforming one problem into another. Here are the steps: Create ...
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  • 5,109
7 votes

How can I quickly find the coordinates of key points?

A single point covers at most 28 points. So $\frac{1000}{28}\approx35.7<n$. Now here's some code that selects random points from the remaining ones until it covers all 1000: ...
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  • 2,648
6 votes
Accepted

Weakness in Maximize

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  • 120k
5 votes

How can I quickly find the coordinates of key points?

An alternate approach to structuring the problem. Since this is Mathematica, we're required to use patterns. I think it is possible to make it more "pattern-ish" Build up the list of points.....
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  • 6,898
4 votes
Accepted

Minimax / Minmax optimization

The problem you wish to solve, that is the one in which you would not need to enumerate the eigenvalues, may not be that easy to solve. However, the one you stated is indeed a convex problem, more ...
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3 votes

Boolean constraint in an interval for FindMinimum

I hope I understood your question correctly. I assume that by "monotonically increasing" you mean increasing in the x and y direction. Here is an example. With two example functions: ...
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  • 24.3k
3 votes
Accepted

Local extrema points of a function of two variables

If $D f(x,y)=0$ and $\mathrm{Hessian}f(x,y)$ is a positive definite matrix,then $f(x,y)$ get the local minimal. If $D f(x,y)=0$ and $\mathrm{Hessian}f(x,y)$ is a negative definite matrix,then $f(x,y)$ ...
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  • 30.6k
3 votes
Accepted

Parametric minimization of a quadratic expression in two variables

Use a replacement rule to replace explicit values of the parameters in the general conditional solution returned by Maximize: ...
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  • 58.4k
2 votes

Steiner Trees for Unit Polygons?

After nearly 4 years I had occasion to again compile GeoSteiner 5.1. I'll publish how I got it working on the Mac in the hope it may help someone else. Proceed as follows on Mac Monterey 12.3.1: ...
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  • 456
1 vote

Finding local minimum of a 2D potential

There is a local minimum. Rationalize parameter and first search for minimum curve with respect to chi. This can be achieved by intermediate substitution of exp term. ...
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  • 15.2k
1 vote

Implementing an optimization algorithm in WL

I managed finally to make a faster and correct version for Jaya: ...
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