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POAlgorithm for sorting numbers summing to a total and respecting criterions in python
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copied!<p>I am trying to do a feed optimisation calculation for animal feeding but I am a rookie in term of python coding.</p> <p>Actually what I try to achieve is compute the less expensive combination of n ingredients by groups of k or less that supply enough of A and B criterions.</p> <p>My problem is that when ingredients number start going up, python hangs in the calculations. So is there a way to have python use more memory or a better algorithm or already available package for those kind of computations. I searched the net for answer but maybe this particular problem has a mathematical name I am unaware of.</p> <p>What I am doing now:</p> <ol> <li>Create the ingredient matrix: each ingredient has a name and then P,A,B,C,D... where P is the price and A,B,C,... are the values for different nutritive elements</li> <li>Create the limit matrix: Each element has a minimum and maximum value of the total mix.</li> <li>Create the objective vector: What I want to obtain for now it is a A=X vector and B=Y vector but I would like to specify C,D, etc. in the future.</li> <li>I then compute all the possible combinations of ingredients summing to a total (usually 1000) and by group of k ingredients.</li> <li>Remove the combinations that do not fit the limit matrix to get the available combination matrix</li> <li>Multiply the ingredient matrix by the combination matrix to get the final composition matrix</li> <li>Remove all the values in the composition matrix that do not fit the objective vector for criterions A and B.</li> <li>Sort the resulting list by price and give the result.</li> </ol> <p>I am using Numpy for most of those operations.</p> <p>The approach (to my knowledge) cannot be a simple linear algebra problem because sometimes there will be no perfect solution which is why the numerical approach was taken in the first place. </p> <p>Thanks</p>

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