Incorporating uncertainty in optimization models gives rise to large, structured mathematical programs. Decomposition procedures are well-suited for parallelization, thus providing a promising venue for solving large ...

We develop a multi-stage stochastic programming model for international portfolio management in a dynamic setting. We model uncertainty in asset prices and exchange rates in terms of scenario trees that reflect the empirical ...

In this paper, a general framework for continuous time power control algorithm under time varying long term fading wireless channels is developed. This contrasts most of the power control algorithms introduced in the ...

The surface of the ocean, and so such quantities as the significant wave height, can be thought of as a random surface in space which develops over time. In this paper, we explore certain types of random fields (in space ...

We develop a stochastic programming model to address in a unified manner a number of interrelated decisions in international portfolio management: optimal portfolio diversification and mitigation of market and currency ...

We examine valuation procedures that can be applied to incorporate options in scenario-based portfolio optimization models. Stochastic programming models use discrete scenarios to represent the stochastic evolution of asset ...

Έχοντας ως κίνητρο την παροχή Ποιότητας Υπηρεσιών (ΠΥ) σε Δίκτυα Επικοινωνιών, η Διατριβή αυτή στοχεύει στην ανάπτυξη πλαισίου για δυναμικό έλεγχο των παραμέτρων σε συστήματα ουρών ούτως ώστε να παρέχεται η απαιτούμενη ΠΥ. ...

Debt restructuring is one of the policy tools available for resolving sovereign debt crises and, while unorthodox, it is not uncommon. We propose a scenario analysis for debt sustainability and integrate it with scenario ...

Stochastic programs with recourse provide an effective modeling paradigm for sequential decision problems with uncertain or noisy data, when uncertainty can be modeled by a discrete set of scenarios. In two-stage problems ...