On integrating data uncertainty and multi-objective optimization: application to problems in disaster relief logistics
Sprache des Vortragstitels:
Englisch
Original Tagungtitel:
ÖGOR ATHEA Workshop
Sprache des Tagungstitel:
Englisch
Original Kurzfassung:
Many optimization problems in the field of disaster relief logistics feature multiple objectives as well as parameter uncertainty. In this talk, we focus on the selection of distribution facilities, using data sets for slow-onset
disasters such as droughts and sudden-onset disasters such as earthquakes. The considered concurrent objectives are cost and population coverage. Uncertain parameters are, e.g., the demand at the population centers or the capacities of the considered facilities. Several different
approaches for dealing with data uncertainty exist. In this talk, we review two-stage stochastic programming, conditional value at risk, and scenario-based adjustable robust optimization. We establish a theoretical relationship between the latter two concepts and we combine the
different approaches with criterion space search schemes, such as the balanced-box method or the epsilon-constraint scheme to account for the multi-objective nature of the problems. Finally, we also show how to integrate the L-shaped method into a bi-objective branch-and-bound
framework to efficiently solve mixed integer bi-objective two-stage stochastic programs. We discuss the obtained results, both from a methodological as well as from a managerial perspective.
Sprache der Kurzfassung:
Englisch
Vortragstyp:
Hauptvortrag / Eingeladener Vortrag auf einer Tagung
Forschungs-