This article introduces a risk-averse stochastic modeling approach for a pre-disaster relief
network design problem under uncertain demand and transportation capacities. The sizes …

The large-scale penetration of variable renewable energy and their generation uncertainties
poses a major challenge for the distribution system operator to efficiently determine the day …

We consider probabilistically constrained stochastic programming problems, in which the
random variables are in the right-hand sides of the stochastic inequalities defining the joint …

We propose a new modeling and solution method for probabilistically constrained
optimization problems. The methodology is based on the integration of the stochastic …

Water and electricity distribution networks are two highly interdependent and critical
infrastructures in the world today. This paper investigates the coupling of water and …

For problems when decisions are taken prior to observing the realization of underlying
random events, probabilistic constraints are an important modeling tool if reliability is a …

In this paper, a model is proposed for the optimal operation of multi-energy microgrids
(MEMGs) in the presence of solar photovoltaics (PV), heterogeneous energy storage (HES) …

We focus on optimization models involving individual chance constraints, in which only the
right-hand side vector is random with a finite distribution. A recently introduced class of such …

With the increasing integration of renewable energy into power networks, the scheduling
and operation of power systems become more challenging, in particular because of the …

Probability constraints are often employed to intuitively define safety of given decisions in
optimization problems. They simply express that a given system of inequalities depending …