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A Two-Phase Heuristic for the Collection of Waste Animal Tissue in a Colombian Rendering Company

  • Eduwin J. Aguirre-GonzalezEmail author
  • Juan G. VillegasEmail author
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 742)

Abstract

This work addresses the planning of the collection of waste animal tissue in a Colombian rendering company. Over a week, the rendering company visits more than 800 slaughterhouses, butchers, and supermarkets in the Aburra’s Valley, the metropolitan area of Medellín (Colombia) to supply their plant (located in the outskirts of the city) with raw material that are transformed into value-added products. The underlying vehicle routing problem have several distinguishing features: periodicity, consistency, clustered customers and heterogeneous fleet. To solve this rich VRP we present a two-phase heuristic. The first phase of the heuristic groups the collection points using a capacitated concentrator location problem (CCLP). Then, in the second phase a mixed integer program schedules the visits of the collection points in each cluster to balance the number of visits performed daily based on the capacities of the available vehicles. These two phases aim at getting consistent and evenly spread visits during the week. Preliminary results with the data of the current operation reveal a savings potential of 5 out of 15 vehicles, and a better spread of the visits over the planning horizon.

Keywords

Clustering Scheduling Rendering Waste collection 

References

  1. 1.
    Aldrich, G., Andreson, D., Basu, L., Bisplinghoff, F.: Lo impresindible del reciclaje todo sobre la industría de los subproductos de origen animal (2009)Google Scholar
  2. 2.
    ANIF: Mercados industriales (2014)Google Scholar
  3. 3.
    Baldacci, R., Battarra, M., Vigo, D.: Routing a heterogeneous fleet of vehicles. In: The Vehicle Routing Problem: Latest Advances and New Challenges, pp. 3–27. Springer, New York (2008)Google Scholar
  4. 4.
    Baldacci, R., Mingozzi, A., Roberti, R.: Recent exact algorithms for solving the vehicle routing problem under capacity and time window constraints. Eur. J. Oper. Res. 218(1), 1–6 (2012)MathSciNetCrossRefzbMATHGoogle Scholar
  5. 5.
    Ballou, R.H.: Business logistics/supply chain management: planning, organizing, and controlling the supply chain. Pearson Education India (2007)Google Scholar
  6. 6.
    Battarra, M., Erdogan, G., Vigo, D.: Exact algorithms for the clustered vehicle routing problem. Oper. Res. 62(1), 58–71 (2014)MathSciNetCrossRefzbMATHGoogle Scholar
  7. 7.
    Bianchi-Aguiar, T., Carravilla, M.A., Oliveira, J.F.: Municipal waste collection in Ponte de Lima, Portugal - a vehicle routing application. OR Insight 25(4), 185–198 (2012). http://link.springer.com/10.1057/ori.2011.23
  8. 8.
    Bramel, J., Simchi-Levi, D.: A location based heuristic for general routing problems. Oper. Res. 43(4), 649–660 (1995)MathSciNetCrossRefzbMATHGoogle Scholar
  9. 9.
    Campbell, A.M., Wilson, J.H.: Forty years of periodic vehicle routing. Networks 63(1), 2–15 (2014). http://doi.wiley.com/10.1002/net.21527
  10. 10.
    Coene, S., Arnout, A., Spieksma, F.C.R.: On a periodic vehicle routing problem. J. Oper. Res. Soc. 61(12), 1719–1728 (2010). http://dx.doi.org/10.1057/jors.2009.154
  11. 11.
    Cordeau, J.F., Laporte, G., Savelsbergh, M.W., Vigo, D.: Vehicle routing. Handb. Oper. Res. Manage. Sci. 14, 367–428 (2007)CrossRefGoogle Scholar
  12. 12.
    Doerner, K.F., Schmid, V.: Survey: matheuristics for rich vehicle routing problems. In: International Workshop on Hybrid Metaheuristics, pp. 206–221. Springer, New York (2010)Google Scholar
  13. 13.
    Ferreira, J.A., Costa, M., Tereso, A., Oliveira, J.A.: A multi-criteria decision support system for a routing problem in waste collection. In: International Conference on Evolutionary Multi-Criterion Optimization, pp. 388–402. Springer, New York (2015)Google Scholar
  14. 14.
    Gendreau, M., Potvin, J.Y., Bräysy, O., Hasle, G., Løkketangen, A.: Metaheuristics for the vehicle routing problem and its extensions: a categorized bibliography. In: The Vehicle Routing Problem: Latest Advances and New Challenges, pp. 143–169. Springer, New York (2008)Google Scholar
  15. 15.
    Gutin, G., Punnen, A.P.: The traveling salesman problem and its variations, vol. 12. Springer Science & Business Media, New York (2006)Google Scholar
  16. 16.
    Irnich, S., Toth, P., Vigo, D.: The family of vehicle routing problems. In: Vehicle Routing: Problems, Methods, and Applications, pp. 1–36. SIAM, Philadelphia (2014)Google Scholar
  17. 17.
    Koç, Ç., Bektaş, T., Jabali, O., Laporte, G.: Thirty years of heterogeneous vehicle routing. Eur. J. Oper. Res. 249(1), 1–21 (2016)MathSciNetCrossRefzbMATHGoogle Scholar
  18. 18.
    Lahyani, R., Coelho, L.C., Khemakhem, M., Laporte, G., Semet, F.: A multi-compartment vehicle routing problem arising in the collection of olive oil in Tunisia. Omega 51, 1–10 (2015). http://dx.doi.org/10.1016/j.omega.2014.08.007
  19. 19.
    Laporte, G., Semet, F.: Classical Heuristics for the Vehicle Routing Problem. Les cahiers du GERAD (1999)Google Scholar
  20. 20.
    Prins, C.: Efficient heuristics for the heterogeneous fleet multitrip VRP with application to a large-scale real case. J. Math. Model. Algorithms 1(2), 135–150 (2002)MathSciNetCrossRefzbMATHGoogle Scholar
  21. 21.
    Sahoo, S., Kim, S., Kim, B.I., Kraas, B., Popov, A.: Routing optimization for waste management. Interfaces 35(1), 24–36 (2005)CrossRefGoogle Scholar
  22. 22.
    Sevaux, M., Sörensen, K.: Hamiltonian paths in large clustered routing problems. In: Proceedings of the EU/MEeting 2008 workshop on Metaheuristics for Logistics and Vehicle Routing, EU/ME 2008, pp. 4:1–4:7. Troyes, France (2008)Google Scholar
  23. 23.
    Tarantilis, C.D., Kiranoudis, C.T.: A meta-heuristic algorithm for the efficient distribution of perishable foods. J. Food Eng. 50(1), 1–9 (2001)CrossRefGoogle Scholar
  24. 24.
    Team, Q.G.D.: Quantum GIS Geographic Information System (2017). http://qgis.osgeo.org
  25. 25.
    Toth, P., Vigo, D.: Vehicle Routing: Problems, Methods, and Applications. SIAM, Philadelphia (2014)CrossRefzbMATHGoogle Scholar
  26. 26.
    Vidal, T., Battarra, M., Subramanian, A., Erdogan, G.: Hybrid metaheuristics for the clustered vehicle routing problem. Comput. Oper. Res. 58, 87–99 (2015)MathSciNetCrossRefzbMATHGoogle Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Departamento de Ingeniería Industrial, Facultad de IngenieríaUniversidad de AntioquiaMedellínColombia

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