Hi all, I'm trying to model a problem but it turned out to be non linear.
A simplified version of the model is written below. Basically it averages the weighted value of all enabled points, provided there are exactly M enabled points. *max sum(i) { enabled[i] * value[i] * weight[i] } / sum(i) { enabled[i] * weight[i] }* *s.t. sum (i) enabled[i] = M* - *value* is a vector of decimal numbers in [0, 1] (precomputed) - *weight* is a vector of decimal numbers in [0, 1] (precomputed) - *enabled* is a vector of either 0 or 1 (decision variable) The model is very simple so I'm guessing there probably is a way to linearize it or some workaround I'm not aware of. Thanks, Matt
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