EURO 2024 Copenhagen
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404. Planning effective emergency responses: K-adjustable robust optimisation for relief prepositioning

Invited abstract in session MC-21: Disaster Response: Search and Rescue, Resource Allocation and Impactful Prepositioning, stream OR in Humanitarian Operations (HOpe).

Monday, 12:30-14:00
Room: 49 (building: 116)

Authors (first author is the speaker)

1. Fabricio Oliveira
Mathematics and Systems Analysis, Aalto University

Abstract

Emergency response refers to the systematic response to an unexpected, disruptive occurrence such as a natural disaster. The response aims to mitigate the consequences of the occurrence by providing the affected region with the necessary supplies. A critical factor for a successful response is its timely execution, but the unpredictable nature of disasters often prevents quick reactionary measures. Preallocating the supplies before the disaster takes place allows for a faster response, but requires more overall resources because the time and place of the disaster are not yet known. This gives rise to a trade-off between how quickly a response plan is executed and how precisely it targets the affected areas. Aiming to capture the dynamics of this trade-off, we develop a $K$-adjustable robust model, which allows a maximum of $K$ second-stage decisions, i.e., response plans. This mitigates tractability issues and allows the decision-maker to seamlessly navigate the gap between the readiness of a proactive yet rigid response and the accuracy of a reactive yet highly adjustable one. The approaches we consider to solve the $K$-adaptable model are threefold: Approximately, via a partition-and-bound method, and optimally via a branch-and-bound method as well as a static robust reformulation in combination with a column-and-constraint generation algorithm. In a computational study, we compare and contrast the different solution approaches and assess their potential.

Keywords

Status: accepted

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