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The Team Orienteering Problem with Overlaps: An Application in Cash Logistics

Author

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  • Christos Orlis

    (Department of Supply Chain Analytics, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, Netherlands)

  • Nicola Bianchessi

    (Department of Supply Chain Analytics, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, Netherlands; Dipartimento di Informatica, Università degli Studi di Milano, 20122 Milan, Italy)

  • Roberto Roberti

    (Department of Supply Chain Analytics, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, Netherlands)

  • Wout Dullaert

    (Department of Supply Chain Analytics, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, Netherlands)

Abstract

The team orienteering problem ( TOP ) aims at finding a set of routes subject to maximum route duration constraints that maximize the total collected profit from a set of customers. Motivated by a real-life automated teller machine cash replenishment problem that seeks for routes maximizing the number of bank account holders having access to cash withdrawal, we investigate a generalization of the TOP that we call the team orienteering problem with overlaps ( TOPO ). For this problem, the sum of individual profits may overestimate the real profit. We present exact solution methods based on column generation and a metaheuristic based on large neighborhood search to solve the TOPO. An extensive computational analysis shows that the proposed solution methods can efficiently solve synthetic and real-life TOPO instances. Moreover, the proposed methods are competitive with the best algorithms from the literature for the TOP. In particular, the exact methods can find the optimal solution of 371 of the 387 benchmark TOP instances, 33 of which are closed for the first time.

Suggested Citation

  • Christos Orlis & Nicola Bianchessi & Roberto Roberti & Wout Dullaert, 2020. "The Team Orienteering Problem with Overlaps: An Application in Cash Logistics," Transportation Science, INFORMS, vol. 54(2), pages 470-487, March.
    • Handle: RePEc:inm:ortrsc:v:54:y:2020:i:2:p:470-487
    DOI: 10.1287/trsc.2019.0923
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    References listed on IDEAS

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    3. Fang, Chao & Han, Zonglei & Wang, Wei & Zio, Enrico, 2023. "Routing UAVs in landslides Monitoring: A neural network heuristic for team orienteering with mandatory visits," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 175(C).

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