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Metaheuristics for the risk-constrained cash-in-transit vehicle routing problem

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  • Talarico, Luca
  • Sörensen, Kenneth
  • Springael, Johan

Abstract

This paper proposes a variant of the well-known capacitated vehicle routing problem that models the routing of vehicles in the cash-in-transit industry by introducing a risk constraint. In the Risk-constrained Cash-in-Transit Vehicle Routing Problem (RCTVRP), the risk of being robbed, which is assumed to be proportional both to the amount of cash being carried and the time or the distance covered by the vehicle carrying the cash, is limited by a risk threshold. A library containing two sets of instances for the RCTVRP, some with known optimal solution, is generated. A mathematical formulation is developed and small instances of the problem are solved by using IBM CPLEX. Four constructive heuristics as well as a local search block composed of six local search operators are developed and combined using two different metaheuristic structures: a multistart heuristic and a perturb-and-improve structure. In a statistical experiment, the best parameter settings for each component are determined, and the resulting heuristic configurations are compared in their best possible setting. The resulting metaheuristics are able to obtain solutions of excellent quality in very limited computing times.

Suggested Citation

  • Talarico, Luca & Sörensen, Kenneth & Springael, Johan, 2015. "Metaheuristics for the risk-constrained cash-in-transit vehicle routing problem," European Journal of Operational Research, Elsevier, vol. 244(2), pages 457-470.
    • Handle: RePEc:eee:ejores:v:244:y:2015:i:2:p:457-470
    DOI: 10.1016/j.ejor.2015.01.040
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    Cited by:

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    2. Hoogeboom, Maaike & Dullaert, Wout, 2019. "Vehicle routing with arrival time diversification," European Journal of Operational Research, Elsevier, vol. 275(1), pages 93-107.
    3. Hughes, Michael S. & Lunday, Brian J. & Weir, Jeffrey D. & Hopkinson, Kenneth M., 2021. "The multiple shortest path problem with path deconfliction," European Journal of Operational Research, Elsevier, vol. 292(3), pages 818-829.
    4. Vidal, Thibaut & Laporte, Gilbert & Matl, Piotr, 2020. "A concise guide to existing and emerging vehicle routing problem variants," European Journal of Operational Research, Elsevier, vol. 286(2), pages 401-416.
    5. Kian, Ramez & Erdoğan, Güneş & de Leeuw, Sander & Sibel Salman, F. & Sabet, Ehsan & Kara, Bahar Y. & Demir, Muhittin H., 2022. "Logistics planning of cash transfer to Syrian refugees in Turkey," European Journal of Operational Research, Elsevier, vol. 296(3), pages 1007-1024.
    6. Zandieh, Fatemeh & Ghannadpour, Seyed Farid & Mazdeh, Mohammad Mahdavi, 2024. "New integrated routing and surveillance model with drones and charging station considerations," European Journal of Operational Research, Elsevier, vol. 313(2), pages 527-547.
    7. Tikani, Hamid & Setak, Mostafa & Demir, Emrah, 2021. "A risk-constrained time-dependent cash-in-transit routing problem in multigraph under uncertainty," European Journal of Operational Research, Elsevier, vol. 293(2), pages 703-730.
    8. Anita Agárdi & László Kovács & Tamás Bányai, 2022. "Mathematical Model for the Generalized VRP Model," Sustainability, MDPI, vol. 14(18), pages 1-22, September.
    9. Allahyari, Somayeh & Yaghoubi, Saeed & Van Woensel, Tom, 2021. "A novel risk perspective on location-routing planning: An application in cash transportation," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 150(C).
    10. Xianlong Ge & Yuanzhi Jin & Long Zhang, 2023. "Genetic-based algorithms for cash-in-transit multi depot vehicle routing problems: economic and environmental optimization," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(1), pages 557-586, January.

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