minimize euclidean distance from sets of points in n-dimensions
问题 Let's look at m points in n-d space- (A solution for 4 points in 3-d space is here: minimize distance from sets of points) a= (x1, y1, z1, ..) b= (x2, y2 ,z2, ..) c= (x3, y3, z3, ..) . . p= (x , y , z, ..) Find point q = c1* a + c2* b + c3* c + .. where c1 + c2 + c3 + .. = 1 and c1, c2, c3, .. >= 0 s.t. euclidean distance pq is minimized. What algorithms can be used ? Idea or pseudocode is enough. (Optimizing performance is a big issue here. Monte Carlo method with all vertices and changing