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 ...

“When solving a very large computational problem, optimization solvers can require significant computational time to find a first feasible solution,” said Dr. Timo Berthold, director of Mixed ...

Quantum computers can solve combinatorial optimization problems more easily than conventional methods, research shows by Helmholtz Association of German Research Centres Editors' notes ...

Conventional quantum algorithms are not feasible for solving combinatorial optimization problems (COPs) with constraints in the operation time of quantum computers. To address this issue ...