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A Large Neighbourhood Search Metaheuristic for the Contagious Disease Testing Problem

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  • Wolfinger, David
  • Gansterer, Margaretha
  • Doerner, Karl F.
  • Popper, Nikolas

Abstract

In late 2019 a new coronavirus disease (COVID-19) emerged, causing a global pandemic within only a few weeks. A crucial factor in the public health response to pandemics is achieving a short turnaround time between a potential case becoming known, specimen collection and availability of a test result. In this article we address a logistics problem that arises in the context of testing potential cases. We assume that specimens can be collected in two ways: either by means of a mobile test-team or by means of a stationary test-team in a test-centre. After the specimens have been collected they must be delivered to a laboratory in order to be analysed. The problem we address aims at deciding how many test-centres to open and where, how many mobile test-teams to use, which suspected cases to assign to a test-centre and which to visit with a mobile test-team, which specimen to assign to which laboratory, and planning the routes of the mobile test-teams. The objective is to minimise the total cost of opening test-centres and routing mobile test-teams. We introduce this new problem, which we call the contagious disease testing problem (CDTP), and present a mixed-integer linear-programming formulation for it. We propose a large neighbourhood search metaheuristic for solving the CDTP and present an extensive computational study to illustrate its performance. Furthermore, we give managerial insights regarding COVID-19 test logistics, derived from problem instances based on real world data.

Suggested Citation

  • Wolfinger, David & Gansterer, Margaretha & Doerner, Karl F. & Popper, Nikolas, 2023. "A Large Neighbourhood Search Metaheuristic for the Contagious Disease Testing Problem," European Journal of Operational Research, Elsevier, vol. 304(1), pages 169-182.
    • Handle: RePEc:eee:ejores:v:304:y:2023:i:1:p:169-182
    DOI: 10.1016/j.ejor.2021.10.028
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    References listed on IDEAS

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