This paper proposes a two-level distributed algorithmic framework for solving the AC optimal
power flow (OPF) problem with convergence guarantees. The presence of highly nonconvex …

In this paper, we study multistage stochastic mixed-integer nonlinear programs (MS-MINLP).
This general class of problems encompasses, as important special cases, multistage …

Many operation optimization problems such as scheduling and assignment of interest to the
automation community are mixed-integer linear programming (MILP) problems. Because of …

First-order methods for solving convex optimization problems have been at the forefront of
mathematical optimization in the last 20 years. The rapid development of this important class …

This paper focuses on the interchange and generation scheduling problem of multi-area
power systems, where decentralized decision procedure is preferred and the uncertainties …

Tube trailers are widely used for distributing liquefied natural gas (LNG) through
transportation networks. When a snowstorm occurs in winter, bad weather conditions may …

We propose a new decomposition method to solve multistage non-convex mixed-integer
(stochastic) nonlinear programming problems (MINLPs). We call this algorithm non-convex …

We propose a new algorithm for solving multistage stochastic mixed integer linear
programming (MILP) problems with complete continuous recourse. In a similar way to cutting …

In this paper, we study adjustable robust optimization (ARO) problems with discrete
uncertainty. Under a very general modeling framework, we show that such two-stage robust …

Most real world applications require dealing with stochasticity like sensor noise or predictive
uncertainty, where formal specifications of desired behavior are inherently probabilistic …