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This article describes a bounding approximation scheme for convex multistage stochastic programs (MSP) that constrain the conditional expectation of some decision-dependent random variables. Expected value constraints of this type are useful for modelling ...
A semi-distributed hydrological model was developed for the upper Rhone River basin in Switzerland to provide 72 h lead time discharge forecasts for the optimization of a multireservoir system during floods The performance of the model is presented and cor ...
Making the best choice when faced with a chain of decisions requires a person to judge both anticipated outcomes and future actions. Although economic decision-making models account for both risk and reward in single-choice contexts, there is a dearth of s ...
Seaport container terminals are source of many interesting large-scale optimization problems, that arise in the management of operations at several decision levels. In this work we study exact methods to solve the Tactical Berth Allocation Problem with Qua ...
The purpose of this master project was to explore decision making process applied to a blackjack game and make the links with facets of impulsivity. The first part of this study goes through the mathematical of this game and presented the optimal policy, c ...
Potential scientific collaboration between Swiss and Colombian academic institutions, based on a bibliographic and visit of Colombian public institutions and universities, with recommendations toward decision makers in both countries ...
Context and activity recognition in complex scenarios is prone to data loss due to disconnections, sensor failure, transmission problems, etc. This generally implies significant changes in the recognition performance. In the case of classifier fusion fault ...
The availability of mobile sociometric sensors allows Computer-Supported Cooperative Work (CSCW) designers the possibility to enhance online meeting support through automatic recognition of conversational context. This paper addresses the task of discrimin ...
Many decision problems exhibit structural properties in the sense that the objective function is a composition of different component functions that can be identified using empirical data. We consider the approximation of such objective functions, subject ...
Dynamic stochastic optimization problems with a large (possibly infinite) number of decision stages and high-dimensional state vectors are inherently difficult to solve. In fact, scenario tree-based algorithms are unsuitable for problems with many stages, ...
