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Robustness in decision aiding

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The search for solutions whose performance is little affected by others nearby or by zones of ignorance imposed on the model constitutes both a practical problem and a source of interesting theoretical difficulties.

The purpose of this research project is the study and the extension of conventional responses to the problem of robustness. These extensions are considered from the conceptual point of view (extending the scenario, development of robust conclusions, considering the notion of robustness not in the worst case, ...), from the algorithmic (to address more general models, notably multi-criteria, to propose efficient methods of resolution, to deepen the questions of complexity and of approximation, ...).

Key words : Robustness, flexibility, precaution, min-max, decision aiding, modeling, multiple-criteria, mathematical programming.

Permanent members of the project : Hassene Aissi, Mohamed Ali Aloulou, Meltem Oztürk, Bernard Roy, Daniel Vanderpooten.

+ Members of the pole " Optimisation combinatoire, algorithmique, données" :
Cristina Bazgan, Virginie Gabrel, Cécile Murat.