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A Decision Support Tool for the Location Routing Problem During the COVID-19 Outbreak in Colombia

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Production Research (ICPR-Americas 2020)

Abstract

During the outbreak of coronavirus disease 2019 (COVID-19) in Bogotá, Colombia, some strategies for dealing with the increasing number of infected people and the level of occupation of intensive care units include the use of Personal Protective Equipment (PPE). PPE is a crucial component for patient care and a priority for protecting healthcare workers. For attending this necessity, the location of distribution centers within the city and the corresponding routes to supply the intensive care units (ICU) with PPE have an important role. Formally, this problem is defined as the Location Routing Problem (LRP). The LRP is an NP-Hard problem that combines the Facility Location Problem (FLP) and the Vehicle Routing Problem with Multiple Depots (MDVRP). This work presents a decision support tool based on a simheuristic method that hybridize an Iterated Local Search (ILS) algorithm with Monte Carlo simulation to deal with the LRP with uncertain demands. Realistic data from Bogotá (Colombia) was retrieved using Google Maps to characterize the geographical distribution of both potential facilities and ICUs, while demands were generated using the uniform probability distribution. Our preliminary results suggest the competitiveness of the algorithm in both the deterministic and the stochastic versions of the LRP.

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References

  1. Gorbalenya, A.E., Baker, S.C., Baric, R.S.: The species severe acute respiratory syndrome-related coronavirus: classifying 2019-nCoV and naming it SARS-CoV-2. Nature Microbiol. 5, 536–544 (2020)

    Article  Google Scholar 

  2. Torrealba-Rodriguez, O., Conde-Gutiérrez, R.A., Hernández-Javier, A.L.: Modeling and prediction of covid-19 in Mexico applying mathematical and computational models. Chaos, Solitons Fractals 138, 582–589 (2020). https://doi.org/10.1016/j.chaos.2020.109946

    Article  MathSciNet  Google Scholar 

  3. Wang, P., Zheng, X., Li, J., Zhu, B.: Prediction of epidemic trends in covid-19 with logistic model and machine learning technics. Chaos, Solitons Fractals, 110058 (2020). https://doi.org/10.1016/j.chaos.2020.110058

  4. Saluddata Secretaria Distrital de Salud. Casos confirmados de covid-19 (Aug 2020). http://saludata.saludcapital.gov.co/osb/index.php/datos-de-salud/enfermedades-trasmisibles/covid19/

  5. Cook, T.M.: Personal protective equipment during the covid-19 pandemic - a narrative review. Anaesthesia 75(75), 920–927 (2020)

    Article  Google Scholar 

  6. Chirico, F., Nucera, G., Magnavita, N.: Covid-19: protecting healthcare workers is a priority. Infect. Control Hosp. Epidemiol. 2020(1), 1–4 (2020)

    Google Scholar 

  7. Juan, A.A., Faulin, J., Grasman, S.E., Rabe, M., Figueira, G.: A review of simheuristics: extending metaheuristics to deal with stochastic combinatorial optimization problems. Oper. Res. Perspect. 2, 62–72 (2015)

    MathSciNet  Google Scholar 

  8. Maranzana, F.E.: On the location of supply points to minimize transport costs. J. Oper. Res. Soc. 15(3), 261–270 (1964)

    Article  Google Scholar 

  9. Salhi, S., Rand, G.K.: The effect of ignoring routes when locating depots. Euro. J. Oper. Res. 39(2), 150–156 (1989)

    Article  MathSciNet  Google Scholar 

  10. Nataraj, S., Ferone, D., Quintero-Araujo, C., Juan, A., Festa, P.: Consolidation centers in city logistics: a cooperative approach based on the location routing problem. Int. J. Ind. Eng. Comput. 10(3), 393–404 (2019)

    Google Scholar 

  11. Almouhanna, A., Quintero-Araujo, C.L., Panadero, J., Juan, A.A., Khosravi, B., Ouelhadj, D.: The location routing problem using electric vehicles with constrained distance. Comput. Opera. Res 115, 104864 (2020)

    Article  MathSciNet  Google Scholar 

  12. Quintero-Araujo, C.L., Caballero-Villalobos, J.P., Juan, A.A., Montoya-Torres, J.R.: A biased-randomized metaheuristic for the capacitated location routing problem. Int. Trans. Oper. Res. 24(5), 1079–1098 (2017)

    Article  MathSciNet  Google Scholar 

  13. Prodhon, C., Prins, C.: A survey of recent research on location-routing problems. Euro. J. Oper. Res. 238, 1–17 (2014)

    Article  MathSciNet  Google Scholar 

  14. Quintero-Araujo, C.L., Guimarans, D., Juan, A.A.:. A simheuristic algorithm for the capacitated location routing problem with stochastic demands. J. Simul. 1–18 (2019)

    Google Scholar 

  15. Shen, C.Y.: Logistic growth modelling of covid-19 proliferation in china and its international implications. Int. J. Infect. Dis. 96, 582–589 (2020)

    Article  Google Scholar 

  16. Loske, D.: The impact of covid-19 on transport volume and freight capacity dynamics: an empirical analysis in German food retail logistics. Trans. Res. Interdiscip. Perspectiv. 6, 100165 (2020). https://doi.org/10.1016/j.trip.2020.100165

  17. Zhang, M.-X., Yan, H.-F., Jia-Yu, W., Zheng, Y.-J.: Quarantine vehicle scheduling for transferring high-risk individuals in epidemic areas. Int. J. Environ. Res. Pub. Health 17(7), 2275 (2020)

    Article  Google Scholar 

  18. Yu, H., Sun, X., Solvang, W.D., Zhao, X.: Reverse logistics network design for effective management of medical waste in epidemic outbreaks: insights from the coronavirus disease 2019 (covid-19) outbreak in Wuhan (China). Int. J. Environ. Res. Pub. Health 17(5), 1770 (2020)

    Article  Google Scholar 

  19. Kaplan, E.H.: Covid-19 scratch models to support local decisions. Manufact. Serv. Oper. Manage. (2020). https://doi.org/10.2139/ssrn.3577867

    Article  Google Scholar 

  20. Prins, C., Prodhon, C., Calvo, R.W.: Solving the capacitated location-routing problem by a grasp complemented by a learning process and a path relinking. 4OR 4, 221–238 (2006)

    Google Scholar 

  21. Quintero-Araújo, C.L., Juan, A.A., Montoya-Torres, J.R., Muñoz-Villamizar, A.: A simheuristic algorithm for horizontal cooperation in urban distribution: Application to a case study in Colombia. In: 2016 Winter Simulation Conference (WSC), pp. 2193–2204 (2016)

    Google Scholar 

  22. Lourenço, H.R., Martin, O.C., Stützle, T.: Iterated local search: framework and applications, pp. 363–397. Springer, Boston (2010). ISBN 978-1-4419-1665-5. https://doi.org/10.1007/978-1-4419-1665-5_12

  23. Osman, I.H.: Metastrategy simulated annealing and tabu search algorithms for the vehicle routing problem. Ann. Oper. Res. 41(4), 421–451 (1993)

    Article  Google Scholar 

  24. Erdoğan, G.: An open source spreadsheet solver for vehicle routing problems. Comput. oper. Res. 84, 62–72 (2017)

    Article  MathSciNet  Google Scholar 

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Acknowledgments

This work has been partially supported by the Master Program in Operations Management and the General Direction of Research from Universidad de La Sabana, grant EICEA-112-2018.

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Correspondence to Carlos L. Quintero-Araújo .

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Martínez-Reyes, A., Quintero-Araújo, C.L., Solano-Charris, E.L. (2021). A Decision Support Tool for the Location Routing Problem During the COVID-19 Outbreak in Colombia. In: Rossit, D.A., Tohmé, F., Mejía Delgadillo, G. (eds) Production Research. ICPR-Americas 2020. Communications in Computer and Information Science, vol 1408. Springer, Cham. https://doi.org/10.1007/978-3-030-76310-7_3

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  • DOI: https://doi.org/10.1007/978-3-030-76310-7_3

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