- Friday 6 Oct 2023, 12:00 - 13:00
- Langeveld building
This paper focuses on a problem emerging at the response phase in the aftermath of a disaster event. The problem consists of finding a fair mechanism to distribute a scarce relief item among different demand points in need, under supply uncertainty. The operations are to be executed during a finite planning horizon partitioned into time periods.
The problem is cast as a multi-period location-inventory problem with a coverage constraint where the uncertainty is incorporated via multi-stage stochastic programming. In particular, two decisions are to be made for every period of the planning horizon: (i) where to locate a limited number of mobile points of distribution and (ii) what quantity to deliver to each demand node.
A demand node can be supplied only if a mobile depot has been located within some maximum distance (or travel time) from the node. The total supply available is time-dependent and not known in advance.
In search for fair solutions, the so-called deprivation cost is considered, which is a measure of the “suffering” of a population for facing a shortage of the relief item. A modeling framework is proposed for the problem and tested using instances built from real data available in the literature. Overall, the results show that the models proposed can better support the decision-making process when fairness is of relevance.
More about Zehranaz
Zehranaz Varol, is currently a PhD candidate in the Department of Industrial Engineering at Bilkent University, Turkey. Her dissertation, titled “Fair Allocation of In-Kind Donations in Post-Disaster Phase”, addresses the problem of equitably distributing scarce resources with uncertain availability in the aftermath of a disaster through the use of mobile points of distribution.
Her research interests include humanitarian logistics problems, equitable resource allocation and stochastic programming. She is committed to addressing critical challenges in disaster relief and leveraging her research to make a positive impact in this field.
Lunch will be provided (vegetarian option included).
Secretariat Econometrics: firstname.lastname@example.org
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