Hannah Bakker (IOR), Florian Diehlmann (IIP)

Beschreibung: 

The objective of Humanitarian Logistics is to provide goods to people in need after the impact of a disaster as fast as possible. However, there is a time lag until resources are available on a large scale since resources are scarce and can only be activated successively. Consequently, decision-makers need to carefully allocate resources to increase the disaster intervention impact. This includes, inter alia, the selection of distribution locations (PoDs) or the allocation of staff to these locations.

In particular, during the early stages of a response to a sudden or gradually evolving crisis, time is a crucial aspect. The number of people in need of support rises steadily while the establishment of a humanitarian supply system requires time. Even though it is crucial to supply as many goods as possible, aspects considering fairness cannot be neglected. One promising approach to include fairness into logistics models is the concept of deprivation levels, which represent an individual’s level of suffering. However, including deprivation costs in logistical models is challenging from modeling, as well as a solution perspective.

A general assumption of humanitarian models that serve beneficiaries over multiple periods is that beneficiaries need to be served in every period. However, a reasonable idea to increase the number of beneficiaries a PoD may cover is to increase the number of goods given to a beneficiary at a particular visit, thus decreasing the frequency with which he/she will return and thus increasing the total amount of beneficiaries that PoD may serve. However, increasing the number of goods either requires increased storage capacities at the PoDs or frequent storage fulfillments. The objective of this Master's thesis is to advance an already existing mathematical program for the PoD installation planning in urban areas to accommodate the idea of increasing the service volume at a single visit to increase the overall throughput at a certain PoD. This will require the consideration of various further aspects that need to be discussed and defined in the beginning.

The topic requires advancing an already existing mathematical program to account for an additional real-life aspect of a humanitarian relief network. There is case study data available for a catastrophe in Berlin, Germany, and the model should be tested and evaluated based on this case study. Depending on the model extension heuristic methods may be needed to solve the model.

Anforderungen: Modellierung, Implementierung, Auswertung

Ansprechpartnerin: Hannah Bakker

Bearbeitungsstatus: (Achtung: nur für Masterarbeiten) frei