In the setting of stochastic recourse programs, we consider the problem of minimizing the probability of total costs exceeding a certain threshold value. The problem is referred to as the minimum risk problem and is posed ...

We develop a multi-stage stochastic program for the optimal dispatch of electric power under uncertain demand in a generation system comprising thermal and pumped storage hydro plants. Based on an abstract duality argument ...

We consider linear mulitstage stochastic integer programs and study their functional and dynamic programming formulations as well as conditions for optimality and stability of solutions. Furthermore, we study the application ...

We propose extensions of traditional expectation-based stochastic integer programs to mean-risk models. Risk is measured by expected deviations of suitable random variables from their means or from preselected targets. We ...

In der vorliegenden Arbeit beschreiben wir einen LP-basierten Branch-and-Bound- und einen Lagrange-Relaxations-Zugang für das Blockauswahlproblem in der Kraftwerkseinsatzplanung, wobei moderne Ansätze und Algorithmen für ...

A multi-stage stochastic programming model for power scheduling under uncertainty in a generation system comprising thermal and pumped-storage hydro units is developed. For its computational solution two different decomposition ...

We consider linear two-stage stochastic programs with mixed-integer recourse. Instead of basing the selection of an optimal first-stage solution on expected costs alone, we include into the objective a risk term reflecting ...

The unit commitment problem in power plant operation planning is addressed. For a real power system comprising coal- and gas-fired thermal and pumped-storage hydroplants a large-scale mixed integer optimization model for ...