Optimization problems can be tricky, but they make the world work better ... In 1847, the French mathematician Augustin-Louis Cauchy was working on a suitably complicated example — astronomical ...

Abstract: Control allocation problems can ... each sample a convex quadratic program approximating the nonlinear program. The method is illustrated by simulated maneuvers for a marine vessel equipped ...

First-order methods for solving quadratic programs (QPs ... support-vector machines (SVM), Lasso regression, Portfolio optimization, equality constrained, and random QP domains) on a broad class of ...

In our case, because the objective function is in the form of minimizing the power, it’s natural to consider it as a quadratic-programming (QP) problem. For example, you can use the quadprog function ...

This paper explores the mathematics behind optimal portfolio construction when relative utility and risk are considered together in a general sense. I derive the portfolio optimization problems when ...

Abstract: This paper presents a neurodynamic optimization approach to bilevel quadratic programming (BQP). Based on the Karush-Kuhn-Tucker (KKT) theorem, the BQP problem is reduced ... Finally, three ...