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Optimal selection of third-party logistics providers using integer programming: a case study of a furniture company storage and distribution

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Abstract

This paper investigates the selection of third-party logistics providers (3PLs) based on the best prices offered by them. The focus is on outbound logistics where 3PLs must have their own distribution centres for storage and picking activities. They must also have suitable trucks for distribution to different small-scale customers. The motivation for this paper is a case study from Germany in which a furniture company with hundreds of small customers in ten zones is seeking one or more 3PLs to do the distribution. A mathematical programming model was built based on integer programming where demand per order can be expressed using exponential distribution in each customer zone. The main contribution of this paper is that it finds the best 3PLs based on the different pricing methods of the various providers; this means including the location problem indirectly using the new integer programming model. The model takes into consideration three different methods of pricing based on the offers of five 3PLs. These different methods make it difficult for the decision makers to choose the best solution, especially if specific trends in demand are expected in the future for some customer zones. The results show that future increases in demand in terms of the number of orders or order size could affect the optimal solution. The best pricing method with the lowest variability in cost over time is selected.

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References

  • Alkhatib, S. F., Darlington, R. I., & Nguyen, T. T. (2015). Logistics service providers (LSPs) evaluation and selection: Literature review and framework development. Strategic Outsourcing: An International Journal, 8(1), 102–134.

    Article  Google Scholar 

  • Alnahhal, M., Ridwan, A., Noche, B. (2014). In-plant milk run decision problems. In: 2014 International Conference on Logistics Operations Management, pp. 85–92. IEEE.

  • Ambrosino, D., & Scutella, M. G. (2005). Distribution network design: New problems and related models. European Journal of Operational Research, 165(3), 610–624.

    Article  Google Scholar 

  • Aragão, D. P., Jr., Novaes, A. G. N., & Luna, M. M. M. (2019). An agent-based approach to evaluate collaborative strategies in milk-run OEM operations. Computers & Industrial Engineering, 129(1), 545–555.

    Article  Google Scholar 

  • Bozarth, C., & Handfield, R. B. (2019). Introduction to operations and supply chain management, global edition, 5/E. Pearson.

    Google Scholar 

  • Brar, G.S., Saini, G. (2011). Milk run logistics: literature review and directions. In 2011 Proceedings of the world congress on engineering, 1(1), 6–8. WCE.

  • Cheung, R. K., & Muralidharan, B. (1999). Impact of dynamic decision making on hub-and-spoke freight transportation networks. Annals of Operations Research, 87, 49–71.

    Article  Google Scholar 

  • Chopra, S. (2019). Supply chain management: strategy, planning, and operation, global edition, 7/E. Pearson.

    Google Scholar 

  • Gray, A. E., Karmarkar, U. S., & Seidmann, A. (1992). Design and operation of an order-consolidation warehouse: Models and application. European Journal of Operational Research, 58(1), 14–36.

    Article  Google Scholar 

  • Hanbazazah, A. S., Abril, L., Erkoc, M., & Shaikh, N. (2019). Freight consolidation with divisible shipments, delivery time windows, and piecewise transportation costs. European Journal of Operational Research, 276(1), 187–201.

    Article  Google Scholar 

  • Hiremath, N. C., Sahu, S., & Tiwari, M. K. (2013). Multi objective outbound logistics network design for a manufacturing supply chain. Journal of Intelligent Manufacturing, 24(6), 1071–1084.

    Article  Google Scholar 

  • Jafari-Eskandari, M., Aliahmadi, A. R., & Khaleghi, G. H. H. (2010). A robust optimization approach for the milk run problem with time windows with inventory uncertainty: An auto industry supplies chain case study. International Journal of Rapid Manufacturing, 1(3), 334–347.

    Article  Google Scholar 

  • Jayaram, J., & Tan, K. C. (2010). Supply chain integration with third-party logistics providers. International Journal of Production Economics, 125(2), 262–271.

    Article  Google Scholar 

  • Jung, D., Semeijn, J., & Ghijsen, P. (2008). Evaluating third party logistics relationships: When provider size matters. Review of Business Research, 8(5), 68–77.

    Google Scholar 

  • Krajewski, L. J., Ritzman, L. P., & Malhotra, M. K. (2018). Operations management: Processes and supply chains (12th ed.). Upper Saddle River: Pearson.

    Google Scholar 

  • Lin, J. R., Nozick, L. K., & Turnquist, M. A. (2006). Strategic design of distribution systems with economies of scale in transportation. Annals of Operations Research, 144(1), 161–180.

    Article  Google Scholar 

  • Liu, J. J., So, S. C. K., Choy, K. L., Lau, H., & Kwok, S. K. (2008). Performance improvement of third-party logistics providers—an integrated approach with a logistics information system. International Journal of Technology Management, 42(3), 226–249.

    Article  Google Scholar 

  • Mao, Z., Huang, D., Fang, K., Wang C., & Lu, D. (2020). Milk-run routing problem with progress-lane in the collection of automobile parts. Annals of Operations Research, 291, 657–684. https://doi.org/10.1007/s10479-019-03218-x.

    Article  Google Scholar 

  • Melo, M. T., Nickel, S., & Saldanha-Da-Gama, F. (2009). Facility location and supply chain management–A review. European Journal of Operational Research, 196(2), 401–412.

    Article  Google Scholar 

  • Owusu Kwateng, K., Manso, J. F., & Osei-Mensah, R. (2014). Outbound logistics management in manufacturing companies in Ghana. Review of Business & Finance Studies, 5(1), 83–92.

    Google Scholar 

  • Roy, J., Pamučar, D., & Kar, S. (2020). Evaluation and selection of third party logistics provider under sustainability perspectives: An interval valued fuzzy-rough approach. Annals of Operations Research, 293, 669–714. https://doi.org/10.1007/s10479-019-03501-x.

    Article  Google Scholar 

  • Sharma, S. K., & Kumar, V. (2015). Optimal selection of third-party logistics service providers using quality function deployment and Taguchi loss function. Benchmarking: An International Journal, 22(7), 1281–1300.

    Article  Google Scholar 

  • Shyam, M. P. (2012). Heuristic modeling approach for inbound and outbound logistics system of an automobile supply chain network. Pragmata: Journal of Human Sciences, 1(1), 1–7.

    Google Scholar 

  • Singh, A. K., Subramanian, N., Pawar, K. S., & Bai, R. (2018). Cold chain configuration design: Location-allocation decision-making using coordination, value deterioration, and big data approximation. Annals of Operations Research, 270(1–2), 433–457.

    Article  Google Scholar 

  • Singh, R. K., Gunasekaran, A., & Kumar, P. (2018). Third party logistics (3PL) selection for cold chain management: A fuzzy AHP and fuzzy TOPSIS approach. Annals of Operations Research, 267(1), 531–553.

    Article  Google Scholar 

  • Taylor, C., de Weck, O. (2006). Integrated transportation network design optimization. In: 47th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference 14th AIAA/ASME/AHS Adaptive Structures Conference 7th, p. 1912.

  • Teo, C. P., & Shu, J. (2004). Warehouse-retailer network design problem. Operations Research, 52(3), 396–408.

    Article  Google Scholar 

  • Trisna, T., Marimin, M., Arkeman, Y., & Sunarti, T. (2016). Multi-objective optimization for supply chain management problem: A literature review. Decision Science Letters, 5(2), 283–316.

    Article  Google Scholar 

  • Vega-Mejía, C. A., Montoya-Torres, J. R., & Islam, S. M. (2019). Consideration of triple bottom line objectives for sustainability in the optimization of vehicle routing and loading operations: A systematic literature review. Annals of Operations Research, 273(1–2), 311–375.

    Article  Google Scholar 

  • Zhang, Y., Lin, W. H., Huang, M., & Hu, X. (2019). Multi-warehouse package consolidation for split orders in online retailing. European Journal of Operational Research, 289(3), 1040–1055.

    Article  Google Scholar 

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Correspondence to Mosab I. Tabash.

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Alnahhal, M., Tabash, M.I. & Ahrens, D. Optimal selection of third-party logistics providers using integer programming: a case study of a furniture company storage and distribution. Ann Oper Res 302, 1–22 (2021). https://doi.org/10.1007/s10479-021-04034-y

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