In this paper a method for solving a mid-term unit commitment problem in a large scale thermal power system is presented. This method is based on Lagrangian relaxation and uses a bundle method for solving the nonsmooth ...

A multistage stochastic programming approach to airline network revenue management is presented. The objective is to determine seatprotection levels for all itineraries, fare classes, point of sales of the airlinenetwork ...

Two-stage stochastic programs with random right-hand side are considered. Optimal values and solution sets are regarded as mappings of the expected recourse functions and their perturbations, respectively. Conditions are ...

We consider multistage stochastic optimization models. Logical or integrality constraints, frequently present in optimization models, limit the application of powerful convex analysis tools. Different Lagrangian relaxation ...

The paper provides a condition for differentiability as well as an equivalent criterion for Lipschitz continuity of singular normal distributions. Such distributions are of interest, for instance, in stochastic optimization ...

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 ...

Modeling several competitive leaders and followers acting in an electricity marketleads to coupled systems of mathematical programs with equilibrium constraints,called equilibrium problems with equilibrium constraints ...

The short-term cost-optimal dispatch of electric power in a generation system under uncertain electricity demand is considered. The system comprises thermal and pumped-storage hydro units. An operation model is developed ...

The paper addresses the unit commitment problem in power plant operation planning. For a real power system comprising coal and gas fired thermal as well as pumped storage hydro plants a largescale mixed integer optimization ...

Stochastic programs that do not only minimize expected cost but also take into account risk are of great interest in many application fields. We consider stochastic programs with risk measures in the objective and study ...