The following algorithm is intended to uniformly sample priority (or criterion) vectors from a transformed version of the simplex (which is a surface in 3d space). The transformation involves taking ...

I have a set of K dimension standard basis vectors and the (K-1)-simplex defined over these vectors. I want to divide this simplex into sub-simplexes which partition the original simplex using ...

I am working on an optimization problem about the WFP where i basically have a set of countries where each contry belongs to a specific region. And each country is also represented by an Emergency ...

I tried to do a simplex algorithm in Python and all the tableaus and values were right but, at the last iteration, there were values on the objective function that were off I'm using sympy and numpy. ...

I am trying to solve a simple simplex tableau using the python library scipy. c = [7, 9, 18, 17] A = [ [2, 4, 5, 7], [ 1, 1, 2, 2], [ 1, 2, 3, 3] ] b = [42, 17, 24] from scipy.optimize ...

I'll get the ball rolling with this: I converted Simplex noise written in java to lua and found myself caught on a potential out of bounds error being reported as an attempt to index a nil value. I've ...

Is there a way to use solver in a way to maximise X wilst using as little of budget Y as possible? Looked onlime but can't find any MOLP videos using excel, mainly just mathematical literature. this ...

I need a way of finding an exact value made of the sum of variables chosen from the population. The algorithm can find just the first solution or all. So we can have 10, 20, or 30 different numbers ...

I am using the following code to find x and y in this linear equation. I was wondering if there is a way to add two more constrains to the following equation? For example, how can we add x>0 , and ...

I want to do something like this: dvar Q [1..10]; maximize min(i in 1..10) Q[i] ; Q has 10 different values which i don´t know, i want that the minimun of all those values be as high as possible But ...

I am trying to use the networkx network_simplex() function with a directed graph. In the official documentation it says: This algorithm is not guaranteed to work if edge weights or demands are ...

I am not sure if what I have done so far is correct, and I need help with the iterative step as I don't understand what is going on in the algorithm. Here is my code. Help to finish this would be much ...

I have a matrix A of dimension 1000x70000. my loss function includes A and I want to find optimal value of A using gradient descent where the constraint is that the rows of A remain in probability ...

Typically when generating seamless Simplex noise the strategy is to go to 4-dimensions (a strategy which has worked well for me in the past when using 2-D Simplex), however I am trying to generate a ...

The Bowyer-Watson algorithm for Delaunay triangulation is known to run in O(n^2) according to the authors, where n is the number of data points in R^d. In addition, the algorithm (for example, as is ...