In this work, we address the modeling and solution of mixed-integer linear multistage
stochastic programming problems involving both endogenous and exogenous uncertain …

Endogenous uncertainty concerns uncertainty which is dependent of decisions such as link
failure in the retrofitting planning application. We propose a marginal-based distributionally …

We introduce a new class of distributionally robust optimization problems under decision-
dependent ambiguity sets. In particular, as our ambiguity sets we consider balls centered on …

A preparedness resource allocation model and an algorithmic approach are presented for a
three-stage stochastic problem for managing natural disaster mitigation. That preparedness …

We study the problem of determining how much finished goods inventory to source from
different capacitated facilities in order to maximize profits resulting from sales of such …

The ability to compare random outcomes based on the decision makers' risk preferences is
crucial to modeling decision-making problems under uncertainty. In this tutorial, the primary …

Decision-making under uncertainty is required in a multiplicity of situations in power system
operation and capacity expansion planning. This thesis investigates the drivers and impact …

Despite multi-stage decision problems being common in production planning, there is a
class of such problems for which a general solution framework does not exist, namely …

This paper introduces a node formulation for multistage stochastic programs with
endogenous (ie, decision-dependent) uncertainty. Problems with such structure arise when …

The growing energy demand in the world, together with the increasing challenges related to
climate change, has sparked an ongoing restructuring of energy systems towards renewable …