L. F. Escudero, M. A. Garín, A. Unzueta
Distributionally robust optimization (DRO) is motivated as a counterpart of the usually unknown underlying probability distribution followed by the uncertainty in dynamic problems. An approach is presented for a variety of stochastic multi-horizon (MH) location problems. The strategic uncertainty is represented in a finite set of stagewise-dependent scenarios for a long-term horizon, where the single- and multi-period operational uncertainty is represented in a finite set of stage-dependent scenarios for a short-term horizon. It is assumed the availability of a Nominal Distribution (ND) for the realization of the strategic parameters in the immediate successor nodeset of any strategic node, and a ND for the realization of the operational parameters in the stages through the multi-horizon scenario tree, from where ambiguity sets are obtained. A mixed binary quadratic DRO-MH modeling paradigm is presented to consider the ambiguity sets under risk averse environments.
Palabras clave: dynamic location under uncertainty, distributionally robust optimization
Programado
Localización (GELOCA3)
13 de junio de 2025 09:00
Sala 3. Maria Rúbies Garrofé