Lift-and-project (L &P) cuts are well-known general 0–1 programming cuts which are typically deployed in branch-and-cut methods to solve MILP problems. In this article, we discuss ways to use these cuts within the framework of Benders' decomposition algorithms for solving two-stage...

<Para ID="Par1">Data for optimization problems often comes from (deterministic) forecasts, but it is naïve to consider a forecast as the only future possibility. A more sophisticated approach uses data to generate alternative future scenarios, each with an attached probability. The basic idea is to estimate...</para>

This paper presents a new heuristic for generating scenarios for two-stage stochastic programs. The method uses copulas to describe the dependence between the marginal distributions, instead of the more common correlations. The heuristic is then tested on a simple portfolio-selection model, and...

In this paper we study the problem of optimization over an integer efficient set of a Multiple Objective Integer Linear Stochastic Programming problem. Once the problem is converted into a deterministic one by adapting the <InlineEquation ID="IEq1"> <EquationSource Format="TEX">$$2$$</EquationSource> </InlineEquation>-levels recourse approach, a new pivoting technique is applied to...</equationsource></inlineequation>

We consider optimization problems for minimizing conditional value-at-risk (CVaR) from a computational point of view, with an emphasis on financial applications. As a general solution approach, we suggest to reformulate these CVaR optimization problems as two-stage recourse problems of...