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Optimization of Green Pickup and Delivery Operations in Multi-depot Distribution Problems

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Computational Logistics (ICCL 2021)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 13004))

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Abstract

In this work, the Multi-Depot Green VRP with Pickups and Deliveries (MDGVRP-PD) is studied. It is a routing optimization problem in which the objective is to construct a set of vehicle routes considering multiple depots and one-to-one pickup and delivery operations that minimize emissions through fuel consumption, which depends on weight and travel distance. In one-to-one problems, goods must be transported between a single origin and its single associated destination. Practical considerations imply addressing the pickup and delivery of customers from multiple depots, where a logistics service company can efficiently combine its resources, thus reducing environmental pollution. To tackle this problem, we develop a mathematical programming formulation and matheuristic approach based on the POPMUSIC (Partial Optimization Metaheuristic under Special Intensification Conditions) framework. The results show that if the weight carried on the routes as part of the fitness measure is considered, our matheuristic approach provide an average percentage improvement in emissions of \(30.79\%\), compared to a fitness measure that only takes into account the distances of the routes.

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References

  1. Abdullahi, H., Reyes-Rubiano, L., Ouelhadj, D., Faulin, J., Juan, A.A.: Modelling and multi-criteria analysis of the sustainability dimensions for the green vehicle routing problem. Eur. J. Oper. Res. 292(1), 143–154 (2021)

    Article  MathSciNet  Google Scholar 

  2. Alvim, A.C.F., Taillard, É.D.: Popmusic for the world location-routing problem. EURO J. Transp. Logist. 2(3), 231–254 (2013)

    Article  Google Scholar 

  3. Archetti, C., Speranza, M.G.: A survey on matheuristics for routing problems. EURO J. Comput. Optim. 2(4), 223–246 (2014). https://doi.org/10.1007/s13675-014-0030-7

    Article  MATH  Google Scholar 

  4. Asghari, M., Mirzapour Al-e-hashem, S.M.J.: A green delivery-pickup problem for home hemodialysis machines; sharing economy in distributing scarce resources. Transp. Res. Part E Logist. Transp. Rev. 134, 101815 (2020)

    Google Scholar 

  5. Battarra, M., Cordeau, J.-F., Iori, M.: Chapter 6: pickup-and-delivery problems for goods transportation, chapter 6, pp. 161–191. SIAM (2014)

    Google Scholar 

  6. Bektaş, T., Ehmke, J.F., Psaraftis, H.N., Puchinger, J.: The role of operational research in green freight transportation. Eur. J. Oper. Res. 274(3), 807–823 (2019)

    Article  MathSciNet  Google Scholar 

  7. Bektaş, T., Laporte, G.: The pollution-routing problem. Transp. Res. Part B Methodol 45(8), 1232–1250 (2011)

    Article  Google Scholar 

  8. Cinar, D., Gakis, K., Pardalos, P.M.: A 2-phase constructive algorithm for cumulative vehicle routing problems with limited duration. Expert Syst. Appl. 56, 48–58 (2016)

    Article  Google Scholar 

  9. Cordeau, J.-F., Gendreau, M., Laporte, G.: A tabu search heuristic for periodic and multi-depot vehicle routing problems. Networks 30(2), 105–119 (1997)

    Article  Google Scholar 

  10. Dantzig, G.B., Ramser, J.H.: The truck dispatching problem. Manag. Sci. 6(1), 80–91 (1959)

    Article  MathSciNet  Google Scholar 

  11. U. DBEIS. Greenhouse gas reporting: Conversion factors 2018. Technical report, UK Department for Business, Energy and Industrial Strategy (2018). Accessed 01 June 2021

    Google Scholar 

  12. Demir, E., Bektaş, T., Laporte, G.: The bi-objective pollution-routing problem. Eur. J. Oper. Res. 232(3), 464–478 (2014)

    Article  MathSciNet  Google Scholar 

  13. Demir, E., Bektaş, T., Laporte, G.: A review of recent research on green road freight transportation. Eur. J. Oper. Res. 237(3), 775–793 (2014)

    Article  Google Scholar 

  14. Erdelić, T., Carić, T.: A survey on the electric vehicle routing problem: Variants and solution approaches. J. Adv. Transp. 2019, 5075671 (2019)

    Article  Google Scholar 

  15. Fan, H., Zhang, Y., Tian, P., Lv, Y., Fan, H.: Time-dependent multi-depot green vehicle routing problem with time windows considering temporal-spatial distance. Comput. Oper. Res. 129, 105211 (2021)

    Article  MathSciNet  Google Scholar 

  16. Friedman, M.: A comparison of alternative tests of significance for the problem of m rankings. Ann. Math. Stat. 11, 86–92 (1940)

    Article  MathSciNet  Google Scholar 

  17. Jabir, E., Panicker, V.V., Sridharan, R.: Design and development of a hybrid ant colony-variable neighbourhood search algorithm for a multi-depot green vehicle routing problem. Transp. Res. Part D Transp. Environ. 57, 422–457 (2017)

    Article  Google Scholar 

  18. Kara, İ, Kara, B.Y., Yetis, M.K.: Energy minimizing vehicle routing problem. In: Dress, A., Xu, Y., Zhu, B. (eds.) COCOA 2007. LNCS, vol. 4616, pp. 62–71. Springer, Heidelberg (2007). https://doi.org/10.1007/978-3-540-73556-4_9

    Chapter  Google Scholar 

  19. İ. Kara, B. Y. Kara, and M. K. Yetiş. Cumulative vehicle routing problems. In: Vehicle Routing Problem, pp. 85–98. IntechOpen (2008)

    Google Scholar 

  20. Kopfer, H.W., Schönberger, J., Kopfer, H.: Reducing greenhouse gas emissions of a heterogeneous vehicle fleet. Flex. Serv. Manuf. J. 26(1), 221–248 (2014)

    Article  Google Scholar 

  21. Lalla-Ruiz, E., Voß, S.: Popmusic as a matheuristic for the berth allocation problem. Ann. Math. Artif. Intell 76(1), 173–189 (2016)

    Article  MathSciNet  Google Scholar 

  22. Lalla-Ruiz, E., Voß, S.: A popmusic approach for the multi-depot cumulative capacitated vehicle routing problem. Optim. Lett. 14, 1–21 (2019)

    MathSciNet  MATH  Google Scholar 

  23. Li, Y., Soleimani, H., Zohal, M.: An improved ant colony optimization algorithm for the multi-depot green vehicle routing problem with multiple objectives. J. Cleaner Prod. 227, 1161–1172 (2019)

    Article  Google Scholar 

  24. Lin, C., Choy, K.L., Ho, G.T., Chung, S.H., Lam, H.: Survey of green vehicle routing problem: past and future trends. Expert Syst. Appl. 41(4), 1118–1138 (2014)

    Article  Google Scholar 

  25. Macrina, G., Laporte, G., Guerriero, F., Di Puglia Pugliese, L.: An energy-efficient green-vehicle routing problem with mixed vehicle fleet, partial battery recharging and time windows. Eur. J. Oper. Res. 276(3), 971–982 (2019)

    Article  MathSciNet  Google Scholar 

  26. McKinnon, A.: Environmental sustainability: a new priority for logistics managers. Kogan (2015)

    Google Scholar 

  27. Moghdani, R., Salimifard, K., Demir, E., Benyettou, A.: The green vehicle routing problem: a systematic literature review. J. Cleaner Prod. 279, 123691 (2021)

    Article  Google Scholar 

  28. Montoya-Torres, J.R., López Franco, J., Nieto Isaza, S., Felizzola Jiménez, H., Herazo-Padilla, N.: A literature review on the vehicle routing problem with multiple depots. Comput. Ind. Eng. 79, 115–129 (2015)

    Article  Google Scholar 

  29. Ostertag, A., Doerner, K.F., Hartl, R.F., Taillard, E.D., Waelti, P.: Popmusic for a real-world large-scale vehicle routing problem with time windows. J. Oper. Res. Soc. 60(7), 934–943 (2009)

    Article  Google Scholar 

  30. Sadati, M.E.H., Çatay, B.: A hybrid variable neighborhood search approach for the multi-depot green vehicle routing problem. Transp. Res. Part E Logist. Transp. Rev. 149, 102293 (2021)

    Article  Google Scholar 

  31. Sartori, C.S., Buriol, L.S.: A study on the pickup and delivery problem with time windows: Matheuristics and new instances. Comput. Oper. Res. 124, 105065 (2020)

    Article  MathSciNet  Google Scholar 

  32. Singh, R.R., Gaur, D.R.: Cumulative VRP: a simplified model of green vehicle routing. In: Cinar, D., Gakis, K., Pardalos, P.M. (eds.) Sustainable Logistics and Transportation. SOIA, vol. 129, pp. 39–55. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-69215-9_3

    Chapter  Google Scholar 

  33. Soysal, M., Çimen, M., Demir, E.: On the mathematical modeling of green one-to-one pickup and delivery problem with road segmentation. J. Cleaner Prod. 174, 1664–1678 (2018)

    Article  Google Scholar 

  34. Suzuki, Y.: A new truck-routing approach for reducing fuel consumption and pollutants emission. Transp. Res. Part D Transp. Environ. 16(1), 73–77 (2011)

    Article  Google Scholar 

  35. Taillard, É.D., Voß, S.: Popmusic – partial optimization metaheuristic under special intensification conditions, pp. 613–629. Springer, Boston (2002). https://doi.org/10.1007/978-1-4615-1507-4_27

  36. Wang, J., Yu, Y., Tang, J.: Compensation and profit distribution for cooperative green pickup and delivery problem. Transp. Res. Part B Methodol. 113, 54–69 (2018)

    Article  Google Scholar 

  37. Wang, Y., Assogba, K., Fan, J., Xu, M., Liu, Y., Wang, H.: Multi-depot green vehicle routing problem with shared transportation resource: integration of time-dependent speed and piecewise penalty cost. J. Cleaner Prod. 232, 12–29 (2019)

    Article  Google Scholar 

  38. Zhang, W., Gajpal, Y., Appadoo, S.S., Wei, Q.: Multi-depot green vehicle routing problem to minimize carbon emissions. Sustainability 12(8), 3500 (2020)

    Article  Google Scholar 

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Acknowledgments

This work has been partially supported by ANID-PFCHA/Doctorado Nacional/2020-21200871, and in part by Proyectos de Línea de Investigación Regular (PI_LIR_2020_67, UTFSM) and Programa de Incentivo a la Iniciación Científica (PIIC, UTFSM).

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Authors and Affiliations

  1. Departamento de Informática, Universidad Técnica Federico Santa María, Valparaíso, Chile

    Alejandro Fernández Gil & Carlos Castro

  2. Department of Industrial Engineering and Business Information Systems, University of Twente, Enschede, The Netherlands

    Eduardo Lalla-Ruiz & Martijn Mes

Authors
  1. Alejandro Fernández Gil
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  2. Eduardo Lalla-Ruiz
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  3. Martijn Mes
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  4. Carlos Castro
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Correspondence to Alejandro Fernández Gil .

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Editors and Affiliations

  1. IEBIS, University of Twente, Enschede, Overijssel, The Netherlands

    Martijn Mes

  2. IEBIS, University of Twente, Enschede, Overijssel, The Netherlands

    Eduardo Lalla-Ruiz

  3. IWI-Institute of Information Systems, University of Hamburg, Hamburg, Germany

    Stefan Voß

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Gil, A.F., Lalla-Ruiz, E., Mes, M., Castro, C. (2021). Optimization of Green Pickup and Delivery Operations in Multi-depot Distribution Problems. In: Mes, M., Lalla-Ruiz, E., Voß, S. (eds) Computational Logistics. ICCL 2021. Lecture Notes in Computer Science(), vol 13004. Springer, Cham. https://doi.org/10.1007/978-3-030-87672-2_32

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  • DOI: https://doi.org/10.1007/978-3-030-87672-2_32

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  • Publisher Name: Springer, Cham

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  • Online ISBN: 978-3-030-87672-2

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