EURO 2024 Copenhagen
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3850. Solution Strategies for the Stochastic Dynamic Contagious Disease Testing Program

Invited abstract in session TA-64: Vehicle Routing Under Uncertainty 2, stream VeRoLog - Vehicle Routing and Logistics.

Tuesday, 8:30-10:00
Room: S16 (building: 101)

Authors (first author is the speaker)

1. Emilio Jose Alarcon Ortega
Business Decisions and Analytics, University of Vienna
2. David Wolfinger
Department of Business Decisions and Analytics, University of Vienna
3. Margaretha gansterer
Klagenfurt University
4. Karl Doerner
Department of Business Decisions and Analytics, University of Vienna

Abstract

In this talk, we present a stochastic and dynamic variant of the Control Disease Testing Program (CDTP) that originated in the late COVID-19 global pandemic. The CDTS was proven to be a key strategy to contain and control the pandemic, where suspected cases required to remain isolated and be tested. These results must be available quickly for the CDTS to be effective. We address the stochastic and dynamic version of the problem remark: repetition of the first sentence, maybe this part can be deleted, where only some suspected cases are known in advance, and new suspected cases could appear randomly throughout the course of the day or planning horizon. When a new suspected case arrives, it must be decided whether to include the new test request in the current plan or reject it. The specimens of the accepted requests must be collected on the same day; either by assigning the case to a time slot in a test-center or by visiting the patient with a mobile test-team. On the other hand, rejected requests must be included in the plan for the next day. The aim of this problem is to decide how many mobile test-teams to use, how many test-centers to open and where, which suspected cases to visit with a mobile test-team and which to assign to a test-center, and design the vehicle routes for the mobile test-teams. To solve this problem, we propose a solution method based on value function approximation and compare the effectiveness of the algorithm with respect to benchmark solution approa

Keywords

Status: accepted

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