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 framework based on advanced AI techniques can solve complex, computationally intensive problems faster and in a more more scalable way than state-of-the-art methods, according to a new study. A ...

The leading approach to the simplex method, a widely used technique for balancing complex logistical constraints, can’t get ...

Algorithms that zero in on solutions to optimization problems are the beating heart of machine reasoning. New results reveal surprising limits. Our lives are a succession of optimization problems.