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A Column Generation Approach for Solving a Green Bi-objective Inventory Routing Problem

  • Carlos FrancoEmail author
  • Eduyn Ramiro López-Santana
  • Germán Méndez-Giraldo
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10022)

Abstract

The aim of this paper is present a multi-objective algorithm embedded with column generation to solve a green bi-objective inventory routing problem. In contrast with the classic Inventory Routing Problem where the main objective is to minimize the total cost overall supply chain network, in the green logistics besides this objective a minimization of the \( CO_{2} \) emisions is included. For solving the bi-objective problem, we proposed the use of NISE (Noninferior Set Estimation) algorithm combined with column generation for reduce the amount of variables in the problem.

Keywords

Green logistics Inventory routing problem Column generation Multi-objective optimization NISE 

Notes

Acknowledgments

We thank Fair Isaac Corporation (FICO) for providing us with Xpress-MP licenses under the Academic Partner Program subscribed with Universidad Distrital Francisco Jose de Caldas (Colombia). Last, but not least, the authors would like to thank the comments of the anonymous referees that significantly improved our paper.

References

  1. 1.
    Federgruen, A., Zipkin, P.: A combined vehicle routing and inventory allocation problem. Oper. Res. 32, 1019–1037 (1984)MathSciNetCrossRefzbMATHGoogle Scholar
  2. 2.
    Archetti, C., Bertazzi, L., Laporte, G., Speranza, M.G.: A branch-and-cut algorithm for a vendor-managed inventory-routing problem. Transp. Sci. 41, 382–391 (2007)CrossRefGoogle Scholar
  3. 3.
    Wakeland, W., Cholette, S., Venkat, K.: Food transportation issues and reducing carbon footprint. In: Boye, J.I., Arcand, Y. (eds.) Green Technologies in Food Production and Processing, pp. 211–236. Springer, Boston (2012)CrossRefGoogle Scholar
  4. 4.
    Bell, W.J., Dalberto, L.M., Fisher, M.L., Greenfield, A.J., Jaikumar, R., Kedia, P., Mack, R.G., Prutzman, P.J.: Improving the distribution of industrial gases with an on-line computerized routing and scheduling optimizer. Interfaces. 13, 4–23 (1983)CrossRefGoogle Scholar
  5. 5.
    Bertazzi, L., Speranza, M.G.: Inventory routing problems: an introduction. EURO J. Transp. Logist. 1, 307–326 (2012)CrossRefGoogle Scholar
  6. 6.
    Savelsbergh, M., Song, J.-H.: An optimization algorithm for the inventory routing problem with continuous moves. Comput. Oper. Res. 35, 2266–2282 (2008)MathSciNetCrossRefzbMATHGoogle Scholar
  7. 7.
    Hemmelmayr, V.C., Doerner, K.F., Hartl, R.F.: A variable neighborhood search heuristic for periodic routing problems. Eur. J. Oper. Res. 195, 791–802 (2009)CrossRefzbMATHGoogle Scholar
  8. 8.
    Aghezzaf, E.-H., Raa, B., Van Landeghem, H.: Modeling inventory routing problems in supply chains of high consumption products. Eur. J. Oper. Res. 169, 1048–1063 (2006)MathSciNetCrossRefzbMATHGoogle Scholar
  9. 9.
    Andersson, H., Hoff, A., Christiansen, M., Hasle, G., Løkketangen, A.: Industrial aspects and literature survey: combined inventory management and routing. Comput. Oper. Res. 37, 1515–1536 (2010)MathSciNetCrossRefzbMATHGoogle Scholar
  10. 10.
    Dubedout, H., Dejax, P., Neagu, N., Yeung, T.: A GRASP for real life inventory routing problem: application to bulk gas distribution. In: 9th International Conference on Modeling, Optimization & SIMulation, pp. 1–11 (2012)Google Scholar
  11. 11.
    Coelho, L.C., Cordeau, J.-F., Laporte, G.: Consistency in multi-vehicle inventory-routing. Transp. Res. Part C: Emerg. Technol. 24, 270–287 (2012)CrossRefGoogle Scholar
  12. 12.
    Coelho, L.C., Laporte, G.: The exact solution of several classes of inventory-routing problems. Comput. Oper. Res. 40, 558–565 (2013)MathSciNetCrossRefGoogle Scholar
  13. 13.
    Solyalı, O., Süral, H.: A branch-and-cut algorithm using a strong formulation and an a priori tour-based heuristic for an inventory-routing problem. Transp. Sci. 45, 335–345 (2011)CrossRefGoogle Scholar
  14. 14.
    Coelho, L.C., Laporte, G.: Optimal joint replenishment, delivery and inventory management policies for perishable products. Comput. Oper. Res. 47, 42–52 (2014)MathSciNetCrossRefGoogle Scholar
  15. 15.
    Niakan, F., Rahimi, M.: A multi-objective healthcare inventory routing problem; a fuzzy possibilistic approach. Transp. Res. Part E: Logist. Transp. Rev. 80, 74–94 (2015)CrossRefGoogle Scholar
  16. 16.
    Geiger, M.J., Sevaux, M.: The biobjective inventory routing problem – problem solution and decision support. In: Pahl, J., Reiners, T., Voß, S. (eds.) INOC 2011. LNCS, vol. 6701, pp. 365–378. Springer, Heidelberg (2011). doi: 10.1007/978-3-642-21527-8_41 CrossRefGoogle Scholar
  17. 17.
    Nolz, P.C., Absi, N., Feillet, D.: Optimization of infectious medical waste collection using RFID. In: Paias, A., Ruthmair, M., Voß, S. (eds.) ICCL 2016. LNCS, vol. 9855, pp. 86–100. Springer, Heidelberg (2011). doi: 10.1007/978-3-642-24264-9_7 CrossRefGoogle Scholar
  18. 18.
    Nolz, P.C., Absi, N., Feillet, D.: A bi-objective inventory routing problem for sustainable waste management under uncertainty. J. Multi-Criteria Decis. Anal. 21, 299–314 (2014)CrossRefzbMATHGoogle Scholar
  19. 19.
    Rahimi, M., Baboli, A., Rekik, Y.: A bi-objective inventory routing problem by considering customer satisfaction level in context of perishable product. In: 2014 IEEE Symposium on Computational Intelligence in Production and Logistics Systems (CIPLS), pp. 91–97. IEEE (2014)Google Scholar
  20. 20.
    Lin, C., Choy, K.L., Ho, G.T.S., Chung, S.H., Lam, H.Y.: Survey of green vehicle routing problem: past and future trends. Expert Syst. Appl. 41, 1118–1138 (2014)CrossRefGoogle Scholar
  21. 21.
    Jabir, E., Panicker, V.V., Sridharan, R.: Multi-objective optimization model for a green vehicle routing problem. Procedia – Soc. Behav. Sci. 189, 33–39 (2015)CrossRefGoogle Scholar
  22. 22.
    Al Dhaheri, N., Diabat, A.: A mathematical programming approach to reducing carbon dioxide emissions in the petroleum refining industry. In: 2010 Second International Conference on Engineering Systems Management and Its Applications (ICESMA), pp. 1–5. IEEE (2010)Google Scholar
  23. 23.
    Alkawaleet, N., Hsieh, Y.-F., Wang, Y.: Inventory routing problem with CO2 emissions consideration. In: Golinska, P. (ed.) Logistics Operations, Supply Chain Management and Sustainability, pp. 611–619. Springer International Publishing, Cham (2014)Google Scholar
  24. 24.
    Mirzapour Al-e-hashem, S.M.J., Rekik, Y.: Multi-product multi-period Inventory Routing Problem with a transshipment option: a green approach. Int. J. Prod. Econ. 157, 80–88 (2014)CrossRefGoogle Scholar
  25. 25.
    Malekly, H.: The inventory pollution-routing problem under uncertainty. In: Fahimnia, B., Bell, M.G.H., Hensher, D.A., Sarkis, J. (eds.) Green Logistics and Transportation, pp. 83–117. Springer International Publishing, Cham (2015)Google Scholar
  26. 26.
    Treitl, S., Nolz, P.C., Jammernegg, W.: Incorporating environmental aspects in an inventory routing problem. A case study from the petrochemical industry. Flex. Serv. Manuf. J. 26, 143–169 (2014)CrossRefGoogle Scholar
  27. 27.
    Toth, P., Vigo, D.: The Vehicle Routing Problem. SIAM, Philadelphia (2002)CrossRefzbMATHGoogle Scholar
  28. 28.
    Cohon, J.L.: Multiobjective Programming and Planning. Academic Press, New York (1978)zbMATHGoogle Scholar

Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  • Carlos Franco
    • 1
    Email author
  • Eduyn Ramiro López-Santana
    • 2
  • Germán Méndez-Giraldo
    • 2
  1. 1.Universidad del RosarioBogotáColombia
  2. 2.Universidad Distrital Francisco José de CaldasBogotáColombia

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