mathematical-optimization,linear-programming,integer-programming,quadratic-programming

Models in this form are actually called bilinear optimization problems. The typical approach to linearizing bilinear terms is through something called the McCormick envelope. Consider variables x and y, where you want x*y in the objective of your maximization problem. If we assume x and y are bounded by xL...

r,mathematical-optimization,quadprog,quadratic-programming

You can do this with the solve.QP function from quadprog. From ?solve.QP, we read that solve.QP solves systems of the form min_b {-d'b + 0.5 b'Db | A'b >= b0}. You are solving a problem of the form min_w {-A'w + pw'Cw | w >= 0, 1'w = 1}. Thus,...

scipy,convex-optimization,convex,quadratic-programming

This is a problem in Quadratic Programming. Python - CVXOPT Matlab - quadprog ...

r,mathematical-optimization,minimization,quadratic-programming

Given the similarities of the optimization problem here to your previous question, I will borrow some language directly from my answer to that question. However they are quite a bit different (the previous problem was a linear programming problem and this is a quadratic programming problem, and the constraints differ),...