Description: Basics of numerical optimization: problem formulation, conditions of optimality, search direction, and step length. Calculus-based techniques for univariate and multivariate optimization.

We investigate risk-averse stochastic optimization problems with a risk-shaping constraint in the form of a stochastic-order relation. Both univariate and multivariate orders are considered. We extend ...

A numerical solution of multivariate normal integrals over a region B is given where the covariance matrix is the sum of a diagonal matrix D and the product of a row vector with its transpose. An ...