Formulation of stochastic optimisation problems and computational algorithms for their solution continue to make steady progress as can be seenfrom an analysis of many developments in this field. The edited volume by Wallace ...

When using the minimax approach one tries to hedge against the worst possible distribution belonging to a specified class P. A suitable stability analysis of results with respect to the choice of this class is an important ...

We formulate a risk-averse two-stage stochastic linear programming problem in which unresolved uncertainty remains after the second stage. The objective function is formulated as a composition of conditional risk measures.We ...

In this paper, we consider optimization problems under probabilistic constraints which aredefined by two-sided inequalities for the underlying normally distributed random vector. Asa main step for an algorithmic solution ...

This paper introduces a new cutting plane method for two-stage stochastic mixed-integer programming (SMIP) called Fenchel decomposition (FD). FD usesa class of valid inequalities termed, FD cuts, which are derived based ...

In this paper, a model for (joint) dynamic chance constraints is proposed and applied to an optimization problem in water reservoir management. The model relies on discretization of the decision variables but keeps the ...

We formulate a portfolio planning model which is based on Second-order Stochastic Dominance as the choice criterion. This model is an enhanced version of the multi-objective model proposed by Roman, Darby-Dowman, and Mitra ...

In many power markets around the world the energy generation decisions result from two-sidedauctions in which producing and consuming agents submit their price-quantity bids. Thedetermination of optimal bids in power markets ...