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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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    1. Stefan Ropke & David Pisinger, 2006. "An Adaptive Large Neighborhood Search Heuristic for the Pickup and Delivery Problem with Time Windows," Transportation Science, INFORMS, vol. 40(4), pages 455-472, November.
    2. Michael Schneider & Michael Drexl, 2017. "A survey of the standard location-routing problem," Annals of Operations Research, Springer, vol. 259(1), pages 389-414, December.
    3. Drexl, Michael & Schneider, Michael, 2015. "A survey of variants and extensions of the location-routing problem," European Journal of Operational Research, Elsevier, vol. 241(2), pages 283-308.
    4. Maximilian Schiffer & Grit Walther, 2018. "An Adaptive Large Neighborhood Search for the Location-routing Problem with Intra-route Facilities," Transportation Science, INFORMS, vol. 52(2), pages 331-352, March.
    5. Prodhon, Caroline & Prins, Christian, 2014. "A survey of recent research on location-routing problems," European Journal of Operational Research, Elsevier, vol. 238(1), pages 1-17.
    6. Eva K. Lee & Chien-Hung Chen & Ferdinand Pietz & Bernard Benecke, 2009. "Modeling and Optimizing the Public-Health Infrastructure for Emergency Response," Interfaces, INFORMS, vol. 39(5), pages 476-490, October.
    7. David Pisinger & Stefan Ropke, 2019. "Large Neighborhood Search," International Series in Operations Research & Management Science, in: Michel Gendreau & Jean-Yves Potvin (ed.), Handbook of Metaheuristics, edition 3, chapter 0, pages 99-127, Springer.
    8. Maximilian Schiffer & Michael Schneider & Grit Walther & Gilbert Laporte, 2019. "Vehicle Routing and Location Routing with Intermediate Stops: A Review," Transportation Science, INFORMS, vol. 53(2), pages 319-343, March.
    9. Schneider, M. & Stenger, A. & Hof, J., 2015. "An Adaptive VNS Algorithm for Vehicle Routing Problems with Intermediate Stops," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 63500, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    Full references (including those not matched with items on IDEAS)

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