Abstract
This article introduces the concept of joint distribution context into the location-routing problem (LRP) to tackle the issue of resource waste and high costs in distribution centers (DCs) for multiple companies. Fixed costs of constructing DCs, fixed costs of hiring vehicles, and routing costs are taken into account when constructing the mixed integer programming (MIP) model. A two-stage algorithm is designed to solve this problem. In the first stage, K-means clustering is used to group demand nodes with vehicle capacity constraints. In the second stage, the simplified LRP model is solved by Lingo, and locations of DCs and routing schemes are obtained. Additionally, a cost-sharing model based on the desirability function is developed to address the cost allocation problem among companies. The results and sensitivity analysis demonstrate that the joint distribution can effectively reduce costs.
Similar content being viewed by others
Explore related subjects
Discover the latest articles, news and stories from top researchers in related subjects.Data availability
Enquiries about data availability should be directed to the authors.
References
Botsman, R.: Defining the sharing economy: what is collaborative consumption–and what isn’t. Fast Company 27(1), 2015 (2015)
Zhang, C., Chen, J., Raghunathan, S.: Two-Sided Platform Competition in a Sharing Economy. Manage. Sci. 68(12), 8909–8932 (2022). https://doi.org/10.1287/mnsc.2022.4302
Liu, G.K., Hu, J.Y., Yang, Y., Xia, S.M., Lim, M.K.: Vehicle routing problem in cold Chain logistics: A joint distribution model with carbon trading mechanisms. Resour. Conserv. and Recycl. 156, 104715 (2020). https://doi.org/10.1016/j.resconrec.2020.104715
Ren, X.Y., Jiang, X.X., Ren, L.Y., Meng, L.: A multi-center joint distribution optimization model considering carbon emissions and customer satisfaction. Math. Biosci. Eng. 20(1), 683–706 (2023). https://doi.org/10.3934/mbe.2023031
Wang, Y., Ma, X.L., Liu, M.W., Gong, K., Liu, Y., Xu, M.Z., Wang, Y.H.: Cooperation and profit allocation in two-echelon logistics joint distribution network optimization. Appl. Soft Comput. 56, 143–157 (2017). https://doi.org/10.1016/j.asoc.2017.02.025
Prins, C.: A simple and effective evolutionary algorithm for the vehicle routing problem. Comput. Oper. Res. 31(12), 1985–2002 (2004). https://doi.org/10.1016/s0305-0548(03)00158-8
Salhi, S., Imran, A., Wassan, N.A.: The multi-depot vehicle routing problem with heterogeneous vehicle fleet: Formulation and a variable neighborhood search implementation. Comput. Oper. Res. 52, 315–325 (2014). https://doi.org/10.1016/j.cor.2013.05.011
Derbel, H., Jarboui, B., Hanafi, S., Chabchoub, H.: Genetic algorithm with iterated local search for solving a location-routing problem. Expert Syst. Appl. 39(3), 2865–2871 (2012). https://doi.org/10.1016/j.eswa.2011.08.146
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(3), 221–238 (2006). https://doi.org/10.1007/s10288-006-0001-9
Barletta, C., Garn, W., Turner, C., Fallah, S.: Hybrid fleet capacitated vehicle routing problem with flexible Monte-Carlo Tree search. Int. J Sys. Sci. Oper. Logist (2023). https://doi.org/10.1080/23302674.2022.2102265
Beasley, J.E.: Route 1st - cluster 2nd methods for vehicle-routing. Omega-Int. J. Manage. Sci. 11(4), 403–408 (1983). https://doi.org/10.1016/0305-0483(83)90033-6
Miranda-Bront, J.J., Curcio, B., Mendez-Diaz, I., Montero, A., Pousa, F., Zabala, P.: A cluster-first route-second approach for the swap body vehicle routing problem. Ann. Oper. Res. 253(2), 935–956 (2017). https://doi.org/10.1007/s10479-016-2233-1
Villalba, A.F.L., La Rotta, E.C.G.: Clustering and heuristics algorithm for the vehicle routing problem with time windows. Int. J. Ind. Eng. Comput. 13(2), 165–184 (2022). https://doi.org/10.5267/j.ijiec.2021.12.002
Barreto, S., Ferreira, C., Paixao, J., Santos, B.S.: Using clustering analysis location-routing in a capacitated problem. Eur. J. Oper. Res. 179(3), 968–977 (2007). https://doi.org/10.1016/j.ejor.2005.06.074
Rui Borges, L., Sérgio, B., Carlos, F., Beatriz Sousa, S.: A decision-support tool for a capacitated location-routing problem. Decision Support Sys. 46(1), 366–375 (2008). https://doi.org/10.1016/j.dss.2008.07.007
Savaser, S.K., Kara, B.Y.: Mobile healthcare services in rural areas: an application with periodic location routing problem. OR Spectrum 44(3), 875–910 (2022). https://doi.org/10.1007/s00291-022-00670-3
Schneider, M., Drexl, M.: A survey of the standard location-routing problem. Ann. Oper. Res. 259(1–2), 389–414 (2017). https://doi.org/10.1007/s10479-017-2509-0
George, D., Ronald, S.: Simultaneous Optimization of Several Response Variables. J. Qual. Technol. 12(4), 214–219 (1980). https://doi.org/10.1080/00224065.1980.11980968
Puschmann, T., Alt, R.: Sharing Economy. Bus. Inf. Syst. Eng. 58(1), 93–99 (2016). https://doi.org/10.1007/s12599-015-0420-2
Cheng, M.: Sharing economy: A review and agenda for future research. Int. J. Hosp. Manage. 57, 60–70 (2016). https://doi.org/10.1016/j.ijhm.2016.06.003
Hossain, M.: Sharing economy: A comprehensive literature review. Int. J. Hosp. Manage. 87, 102470 (2020). https://doi.org/10.1016/j.ijhm.2020.102470
Cao, E.R., Chen, G.Z.: Information sharing motivated by production cost reduction in a supply chain with downstream competition. Nav. Res. Logist. 68(7), 898–907 (2021). https://doi.org/10.1002/nav.21977
Guo, H., Yang, C.C., Liu, B.B., Yang, F.: Performance-based contracts in the sharing economy: A supply chain framework with application of Internet of Things. Ann. Oper. Res. 326(SUPPL 1), 1–1 (2023). https://doi.org/10.1007/s10479-021-04144-7
Gansterer, M., Hartl, R.F., Tzur, M.: Transportation in the Sharing Economy. Transp. Sci. 56(3), 567–570 (2022). https://doi.org/10.1287/trsc.2022.1143
Choi, T.M., He, Y.Y.: Peer-to-peer collaborative consumption for fashion products in the sharing economy: Platform operations. Transportation research part e-logistics and transportation review 126, 49–65 (2019). https://doi.org/10.1016/j.tre.2019.03.016
Zhou, Z.N., Wan, X.: Does the Sharing Economy Technology Disrupt Incumbents? Exploring the Influences of Mobile Digital Freight Matching Platforms on Road Freight Logistics Firms. Prod. Oper. Manag. 31(1), 117–137 (2022). https://doi.org/10.1111/poms.13491
Li, Y.S., Zhang, G.Z., Pang, Z.B., Li, L.F.: Continuum approximation models for joint delivery systems using trucks and drones. Enterprise Information Systems 14(4), 406–435 (2020). https://doi.org/10.1080/17517575.2018.1536928
Hsu, C.I., Chen, W.T., Wu, W.J.: Optimal delivery cycles for joint distribution of multi-temperature food. Food Control 34(1), 106–114 (2013). https://doi.org/10.1016/j.foodcont.2013.04.003
Ostermeier, M., Henke, T., Hübner, A., Wäscher, G.: Multi-compartment vehicle routing problems: State-of-the-art, modeling framework and future directions. Eur. J. Oper. Res. 292(3), 799–817 (2021). https://doi.org/10.1016/j.ejor.2020.11.009
Shi, Y., Chen, M., Qu, T., Liu, W., Cai, Y.J.: Digital connectivity in an innovative joint distribution system with real-time demand update. Comput. Indus. 123, 103275 (2020). https://doi.org/10.1016/j.compind.2020.103275
Ouhader, H., El Kyal, M.: Combining Facility Location and Routing Decisions in Sustainable Urban Freight Distribution under Horizontal Collaboration: How Can Shippers Be Benefited? Math. Probl. Eng. 2017, 8687515 (2017). https://doi.org/10.1155/2017/8687515
Watson-Gandy, C.D.T., Dohrn, P.J.: Depot location with van salesmen — A practical approach. Omega 1(3), 321–329 (1973). https://doi.org/10.1016/0305-0483(73)90108-4
Nagy, G., Salhi, S.: Nested Heuristic Methods for the Location-Routeing Problem. J. Oper. Res. Soc. 47(9), 1166–1174 (1996). https://doi.org/10.1057/jors.1996.144
Lim, A., Wang, F.: Multi-Depot Vehicle Routing Problem: A One-Stage Approach. IEEE Trans. Autom. Sci. Eng. 2(4), 397–402 (2005). https://doi.org/10.1109/tase.2005.853472
Wu, T.-H., Low, C., Bai, J.-W.: Heuristic solutions to multi-depot location-routing problems. Comput. Oper. Res. 29(10), 1393–1415 (2002). https://doi.org/10.1016/S0305-0548(01)00038-7
Nagy, G., Salhi, S.: Location-routing: Issues, models and methods. Eur. J. Oper. Res. 177(2), 649–672 (2007). https://doi.org/10.1016/j.ejor.2006.04.004
Prodhon, C., Prins, C.: A survey of recent research on location-routing problems [Review]. Eur. J. Oper. Res. 238(1), 1–17 (2014). https://doi.org/10.1016/j.ejor.2014.01.005
Tadaros, M., Migdalas, A.: Bi- and multi-objective location routing problems: classification and literature review. Oper. Res. Int. Journal 22(5), 4641–4683 (2022). https://doi.org/10.1007/s12351-022-00734-w
Belenguer, J.-M., Benavent, E., Prins, C., Prodhon, C., Wolfler Calvo, R.: A Branch-and-Cut method for the Capacitated Location-Routing Problem. Comput. Oper. Res. 38(6), 931–941 (2011). https://doi.org/10.1016/j.cor.2010.09.019
Baldacci, R., Mingozzi, A., Wolfler Calvo, R.: An exact method for the capacitated location-routing problem. Oper. Res. 59(5), 1284–1296 (2011)
Prins, C., Prodhon, C., Ruiz, A., Soriano, P., Wolfler Calvo, R.: Solving the Capacitated Location-Routing Problem by a Cooperative Lagrangean Relaxation-Granular Tabu Search Heuristic. Transp. Sci. 41(4), 470–483 (2007). https://doi.org/10.1287/trsc.1060.0187
Özyurt, Z., Aksen, D.: Solving the multi-depot location-routing problem with lagrangian relaxation. Extending the horizons: Advances in computing, optimization, and decision technologies 37, 125–144 (2007)
Contardo, C., Cordeau, J.-F., Gendron, B.: A GRASP+ ILP-based metaheuristic for the capacitated location-routing problem. J Heuristics 20, 1–38 (2014)
Chen, X., Chen, B.: Cost-effective designs of fault-tolerant access networks in communication systems. Networks 53(4), 382–391 (2009)
Yin, R.Y., Lu, P.X.: A Cluster-First Route-Second Constructive Heuristic Method for Emergency Logistics Scheduling in Urban Transport Networks. Sustainability 14(4), 2301 (2022). https://doi.org/10.3390/su14042301
Lam, M., Mittenthal, J.: Capacitated hierarchical clustering heuristic for multi depot location-routing problems. Int. J. Log. Res. Appl. 16(5), 433–444 (2013)
Schneider, M., Löffler, M.: Large Composite Neighborhoods for the Capacitated Location-Routing Problem. Transp. Sci. 53(1), 301–318 (2019). https://doi.org/10.1287/trsc.2017.0770
Perl, J., Daskin, M.S.: A warehouse location-routing problem. Transport. Res. B 19(5), 381–396 (1985)
Liu, X.T., Zhang, K., Chen, B.K., Zhou, J., Miao, L.X.: Analysis of logistics service supply chain for the one belt and one road initiative of China. Transportation Research Part e-logistics and Transportation Review 117, 23–39 (2018). https://doi.org/10.1016/j.tre.2018.01.019
Jiang, L., Wang, Y., Liu, D.M.: Logistics cost sharing in supply chains involving a third-party logistics provider. CEJOR 24(1), 207–230 (2016). https://doi.org/10.1007/s10100-014-0348-5
Desrochers, M., Laporte, G.: Improvements and extensions to the Miller-Tucker-Zemlin subtour elimination constraints. Oper. Res. Lett. 10(1), 27–36 (1991). https://doi.org/10.1016/0167-6377(91)90083-2
Rousseeuw, P.J.: Silhouettes: A graphical aid to the interpretation and validation of cluster analysis. J. Comput. Appl. Math. 20, 53–65 (1987). https://doi.org/10.1016/0377-0427(87)90125-7
Funding
Fundamental Research Funds for the Central Universities, China, Grant ID:2023JBMC005. The authors would like to express his gratitude to the reviewers for their time and expertise.
Author information
Authors and Affiliations
Contributions
Binghui Qie and Zhiwei Sun wrote the main manuscript text. Xun Weng collected the data and supervised. Minyu Jin contributed data or analysis tools. Zhiwei Sun Performed the analysis. Runfeng Yu and Minyu Jin conceived and designed the analysis. All authors reviewed the manuscript.
Corresponding author
Ethics declarations
Competing interests
The authors declare no competing interests.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Qie, B., Weng, X., Sun, Z. et al. Location-routing and cost-sharing models under joint distribution. Cluster Comput 27, 5879–5891 (2024). https://doi.org/10.1007/s10586-024-04282-0
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10586-024-04282-0