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Yet Another Math Programming Consultant

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I don't see this that often: a solver that completely hangs. 


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In the previous post, I discussed covering \(k\) of \(n\) 2d points with the smallest possible rectangle. Minimizing the area yields a nonconvex quadratic objective. Solving these models requires global solvers. If we use the perimeter as a measure of size, the problem becomes linear. An example suggested that the solutions of these two approaches are similar. It certai...

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Finding the smallest axis-aligned rectangle that contains all \(n\) given points is very easy. We can simply do:
\[\begin{align}& {\color{darkred}x}_{lo} := \min_i {\color{darkblue}p}_{i,x} \\ & {\color{darkred}x}_{up} := \max_i {\color{darkblue}p}_{i,x} \\ &  {\color{darkred}y}_{lo} := \min_i {\color{darkblue}p}_{i,y} \\ &{\color{darkred}y}_{up} := \max...

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