Abstract The Unit Commitment problem in energy management aims at finding the optimal
production schedule of a set of generation units, while meeting various system-wide …

We introduce a new method for solving nonlinear continuous optimization problems with
chance constraints. Our method is based on a reformulation of the probabilistic constraint as …

Probability constraints are a popular modelling mechanism in applications. They help to
model feasible decisions when the latter are taken prior to observing uncertainty and both …

Adaptability to various driving conditions (TCs) is one of the essential indicators to assess
the optimality of power management strategies (PMSs) of plug-in hybrid electric vehicles …

Chance-constrained programs (CCPs) constitute a difficult class of stochastic programs due
to its possible nondifferentiability and nonconvexity even with simple linear random …

In optimal control problems, often initial data are required that are not known exactly in
practice. In order to take into account this uncertainty, we consider optimal control problems …

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 …

In this work we consider probability functions working on parameter dependent sets that are
given as an intersection of convex sets and their complements. Such an underlying structure …

Probability functions are a powerful modelling tool when seeking to account for uncertainty
in optimization problems. In practice, such uncertainty may result from different sources for …

In decision-making problems under uncertainty, probability constraints are a valuable tool
for expressing safety of decisions. They result from taking the probability measure of a given …