Did you consider yourself a mathematician the last time you sat down to solve a Sudoku puzzle? It’s certainly a mentally ...

In this work, we present a robust optimization method that is suited for unconstrained problems with a nonconvex cost function as well as for problems based on simulations, such as large partial ...

This paper gives general conditions under which a collection of optimization problems, with the objective function and the constraint set depending on a parameter, has optimal solutions that are an ...

Optimization problems in calculus are always asking to maximize or minimize some quantity. Typical phrases that indicate an optimization problem include: "Find the largest ..." or "Find the minimum ..

This property has a straightforward geometric interpretation. Thus, any optimization problem with a quadratic objective can be decomposed into two separate problems: the unconstrained minimization of ...