Skip to main content
SpringerLink
Log in

Leader-based diffusion optimization model in transportation service procurement under heterogeneous drivers’ collaboration networks

  • Original Research
  • Published:
Annals of Operations Research Aims and scope Submit manuscript

Abstract

One of the key issues in transportation systems is allocating shipping orders to the most appropriate drivers in the shortest time and with the maximum profit. Many studies were carried out in the transportation service procurement process for allocating orders, but none of them considered driver-to-driver interactions and applied information diffusion concepts as a framework to maximize the profit, due to the lack of a framework to model the interactions. In this paper, we present a weighted drivers’ collaboration network to form the interactions. To predict the behavior of drivers, a new community detection algorithm is developed to extract communities and their leaders in terms of the speed and power of receiving and diffusing shipping orders. In addition, we present a profit maximization model that utilizes the information diffusion power of community leaders. The results show the model is able to allocate shipping orders to the most suitable drivers in the shortest possible time and with the highest profit. To demonstrate the performance of the developed algorithm, we present a numerical example. Finally, a case study is applied to solve the optimization problem. The results show that the optimized behavior of companies in allocating orders to drivers is based on their risk level, reputation, and the average number of their customers.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12

Similar content being viewed by others

Notes

  1. https://networkdata.ics.uci.edu/.

  2. C. L. DuBois and P. Smyth, “UCI network data repository,” Web page http//networkdata. ics. uci. edu, 2008.

References

  • Al Hla, Y. A., Othman, M., & Saleh, Y. (2019). Optimising an eco-friendly vehicle routing problem model using regular and occasional drivers integrated with driver behaviour control. Journal of Cleaner Production. https://doi.org/10.1016/j.jclepro.2019.06.156

    Article  Google Scholar 

  • Badiee, A., & Ghazanfari, M. (2018). A monopoly pricing model for diffusion maximization based on heterogeneous nodes and negative network externalities (Case study: A novel product). Decision Science Letters. https://doi.org/10.5267/j.dsl.2017.8.001

    Article  Google Scholar 

  • Badiee, A., & Ghazanfari, M. (2019). Development of a monopoly pricing model for diffusion maximization in fuzzy weighted social networks with negative externalities of heterogeneous nodes using a case study. Neural Computing and Applications, 31(10), 6287–6301.

    Article  Google Scholar 

  • Badiee, A., Kalantari, H., Ghazanfari, M., Fathian, M., & Shahanaghi, K. (2020). Introducing drivers’ collaboration network: A two-layers social network perspective in road transportation system analysis. Research in Transportation Business and Management. https://doi.org/10.1016/j.rtbm.2020.100532

    Article  Google Scholar 

  • Buer, T., & Kopfer, H. (2014). A Pareto-metaheuristic for a bi-objective winner determination problem in a combinatorial reverse auction. Computers and Operations Research. https://doi.org/10.1016/j.cor.2013.04.004

    Article  Google Scholar 

  • Buer, T., & Pankratz, G. (2010). Solving a bi-objective winner determination problem in a transportation procurement auction. Logistics Research. https://doi.org/10.1007/s12159-010-0031-8

    Article  Google Scholar 

  • Chi, C. (2015). Mathematical programming approaches to home healthcare nurse routing problem and truckload transportation procurement via combinatorial auctions. Doctoral dissertation, Pennsylvania State University.

  • Feki, Y., Hajji, A., & Rekik, M. (2016). A hedging policy for carriers’ selection under availability and demand uncertainty. Transportation Research Part e: Logistics and Transportation Review. https://doi.org/10.1016/j.tre.2015.11.011

    Article  Google Scholar 

  • Fern, X. Z., & Brodley, C. E. (2004). Solving cluster ensemble problems by bipartite graph partitioning. In Proceedings, Twenty-First International Conference on Machine Learning, ICML. https://doi.org/10.1145/1015330.1015414

    Article  Google Scholar 

  • Hammami, F., Rekik, M., & Coelho, L. C. (2019). Exact and heuristic solution approaches for the bid construction problem in transportation procurement auctions with a heterogeneous fleet. Transportation Research Part e: Logistics and Transportation Review. https://doi.org/10.1016/j.tre.2019.05.009

    Article  Google Scholar 

  • Hammami, F., Rekik, M., & Coelho, L. C. (2020). The combinatorial bid construction problem with stochastic prices for transportation services procurement. Faculté des sciences de l’administration.

  • Hu, Q., Zhang, Z., & Lim, A. (2016). Transportation service procurement problem with transit time. Transportation Research Part b: Methodological. https://doi.org/10.1016/j.trb.2016.01.007

    Article  Google Scholar 

  • Ignatius, J., Hosseini-Motlagh, S. M., Goh, M., Sepehri, M. M., Mustafa, A., & Rahman, A. (2014). Multiobjective combinatorial auctions in transportation procurement. Mathematical Problems in Engineering. https://doi.org/10.1155/2014/951783

    Article  Google Scholar 

  • Jothi Basu, R., Bai, R., & Palaniappan, P. L. K. (2015a). A strategic approach to improve sustainability in transportation service procurement. Transportation Research Part e: Logistics and Transportation Review. https://doi.org/10.1016/j.tre.2014.10.015

    Article  Google Scholar 

  • Jothi Basu, R., Subramanian, N., & Cheikhrouhou, N. (2015b). Review of full truckload transportation service procurement. Transport Reviews, 35(5), 599–621. https://doi.org/10.1080/01441647.2015.1038741

    Article  Google Scholar 

  • Kalantari, H., Badiee, A., Dezhboro, A., Mohammadi, H., & Tirkolaee, E. B. (2022). A fuzzy profit maximization model using communities viable leaders for information diffusion in dynamic drivers collaboration networks. IEEE Transactions on Fuzzy Systems. https://doi.org/10.1109/TFUZZ.2022.3155275

    Article  Google Scholar 

  • Kalantari, H., Badiee, A., & Ghazanfari, M. (2014). A new heuristic model for fuzzy transfer point location problem. Journal of Uncertain Systems, 8(1), 31–43.

    Google Scholar 

  • Kermani, M. A. M. A., Badiee, A., Aliahmadi, A., Ghazanfari, M., & Kalantari, H. (2016). Introducing a procedure for developing a novel centrality measure (Sociability Centrality) for social networks using TOPSIS method and genetic algorithm. Computers in Human Behavior, 56, 295–305. https://doi.org/10.1016/j.chb.2015.11.008

    Article  Google Scholar 

  • Kuyzu, G., Akyol, Ç. G., Ergun, Ö., & Savelsbergh, M. (2015). Bid price optimization for truckload carriers in simultaneous transportation procurement auctions. Transportation Research Part b: Methodological. https://doi.org/10.1016/j.trb.2014.11.012

    Article  Google Scholar 

  • Kwon, R. H., Lee, C.-G., & Ma, Z. (2005). An integrated combinatorial auction mechanism for truckload transportation procurement. University of Toronto.

    Google Scholar 

  • Lafkihi, M., Pan, S., & Ballot, E. (2017). Mechanisms for freight transportation service procurement: A literature-based analysis. In The 47th International conference on computers & industrial engineering (CIE47).

  • Lee, C. G., Kwon, R. H., & Ma, Z. (2007). A carrier’s optimal bid generation problem in combinatorial auctions for transportation procurement. Transportation Research Part e: Logistics and Transportation Review. https://doi.org/10.1016/j.tre.2005.01.004

    Article  Google Scholar 

  • Li, Y., Chen, H., & Prins, C. (2016). Adaptive large neighborhood search for the pickup and delivery problem with time windows, profits, and reserved requests. European Journal of Operational Research. https://doi.org/10.1016/j.ejor.2015.12.032

    Article  Google Scholar 

  • Lim, A., Qin, H., & Xu, Z. (2012). The freight allocation problem with lane cost balancing constraint. European Journal of Operational Research. https://doi.org/10.1016/j.ejor.2011.08.028

    Article  Google Scholar 

  • Lim, A., Wang, F., & Xu, Z. (2006). A transportation problem with minimum quantity commitment. Transportation Science. https://doi.org/10.1287/trsc.1050.0123

    Article  Google Scholar 

  • Ma, Z., Kwon, R. H., & Lee, C.-G. (2010). A stochastic programming winner determination model for truckload procurement under shipment uncertainty. Transportation Research Part e: Logistics and Transportation Review, 46(1), 49–60.

    Article  Google Scholar 

  • Mamaghani, E. J., Chen, H., Prins, C., & Demir, E. (2019). An improved tabu search algorithm for a multi-period bid generation problem with the consideration of delivery lead time. IFAC-PapersOnLine. https://doi.org/10.1016/j.ifacol.2019.11.599

    Article  Google Scholar 

  • Olcaytu, E., & Kuyzu, G. (2019). Location-based distribution estimation for stochastic bid price optimization. Transportation Letters, 13, 1–15.

    Google Scholar 

  • Othmane, I. Ben, Mellouli, S., & Rekik, M. (2019). Reputation-Based Winner Determination Problem in Centralized Combinatorial Auctions for the Procurement of Transportation Services. CIRRELT.

  • Qian, X., Chan, F. T. S., Yin, M., Zhang, Q., Huang, M., & Fu, X. (2020). A two-stage stochastic winner determination model integrating a hybrid mitigation strategy for transportation service procurement auctions. Computers and Industrial Engineering. https://doi.org/10.1016/j.cie.2020.106703

    Article  Google Scholar 

  • Rekik, Monia, Desaulniers, G., Elhallaoui, I., & Saddoune, M. (2017). An exact solution approach for bid construction in truckload transportation procurement auctions with side constraints. GERAD, École des hautes études commerciales.

  • Rekik, M., & Mellouli, S. (2012). Reputation-based winner determination problem for combinatorial transportation procurement auctions. Journal of the Operational Research Society. https://doi.org/10.1057/jors.2011.108

    Article  Google Scholar 

  • Remli, N., & Rekik, M. (2013). A robust winner determination problem for combinatorial transportation auctions under uncertain shipment volumes. Transportation Research Part c: Emerging Technologies. https://doi.org/10.1016/j.trc.2013.07.006

    Article  Google Scholar 

  • Suthers, D., Fusco, J., Schank, P., Chu, K. H., & Schlager, M. (2013). Discovery of community structures in a heterogeneous professional online network. In Proceedings of the Annual Hawaii International Conference on System Sciences. https://doi.org/10.1109/HICSS.2013.179

    Article  Google Scholar 

  • Tomasini, M. (2015). An introduction to multilayer networks (pp. 1–14). BioComplex Laboratory, Florida Institute of Technology.

    Google Scholar 

  • Triki, C. (2021). Using combinatorial auctions for the procurement of occasional drivers in the freight transportation: A case-study. Journal of Cleaner Production. https://doi.org/10.1016/j.jclepro.2021.127057

    Article  Google Scholar 

  • Triki, C., Oprea, S., Beraldi, P., & Crainic, T. G. (2014). The stochastic bid generation problem in combinatorial transportation auctions. European Journal of Operational Research. https://doi.org/10.1016/j.ejor.2013.06.013

    Article  Google Scholar 

  • Wang, X., & Xia, M. (2005). Combinatorial bid generation problem for transportation service procurement. Transportation Research Record: Journal of the Transportation Research Board. https://doi.org/10.1177/0361198105192300120

    Article  Google Scholar 

  • Xu, S. X., & Huang, G. Q. (2013). Transportation service procurement in periodic sealed double auctions with stochastic demand and supply. Transportation Research Part b: Methodological. https://doi.org/10.1016/j.trb.2013.07.015

    Article  Google Scholar 

  • Yakoubi, Z., & Kanawati, R. (2014). LICOD: A Leader-driven algorithm for community detection in complex networks. Vietnam Journal of Computer Science. https://doi.org/10.1007/s40595-014-0025-6

    Article  Google Scholar 

  • Yan, F., Ma, Y., Xu, M., & Ge, X. (2018). Transportation service procurement bid construction problem from less than truckload perspective. Mathematical Problems in Engineering, 1728512. https://doi.org/10.1155/2018/1728512

  • Yan, F., Chen, K., & Xu, M. (2020). A bid generation problem for combinatorial transportation auctions considering in-vehicle consolidations. Asia Pacific Journal of Marketing and Logistics. https://doi.org/10.1108/APJML-09-2019-0556

    Article  Google Scholar 

  • Yan, F., Ma, Y., & Feng, C. (2018a). A bi-level programming for transportation services procurement based on combinatorial auction with fuzzy random parameters. Asia Pacific Journal of Marketing and Logistics. https://doi.org/10.1108/APJML-07-2017-0154

    Article  Google Scholar 

  • Yan, F., Ma, Y., Xu, M., & Ge, X. (2018b). Transportation service procurement bid construction problem from less than truckload perspective. Mathematical Problems in Engineering, 2018, 1728512. https://doi.org/10.1155/2018/1728512

    Article  Google Scholar 

  • Yan, F., Xu, M., Ma, Y., & Yu, H. (2017). Price optimization for transportation service procurement with fuzzy random shipments: From shipper’s perspective. Transportation Letters, 9(5), 258–275.

    Article  Google Scholar 

  • Yang, F., & Huang, Y. H. (2020). Linearization technique with superior expressions for centralized planning problem with discount policy. Physica a: Statistical Mechanics and Its Applications, 542, 122746. https://doi.org/10.1016/j.physa.2019.122746

    Article  Google Scholar 

  • Yang, F., Huang, Y. H., & Li, J. (2019). Alternative solution algorithm for winner determination problem with quantity discount of transportation service procurement. Physica a: Statistical Mechanics and Its Applications, 535, 122286. https://doi.org/10.1016/j.physa.2019.122286

    Article  Google Scholar 

  • Zhang, B., Ding, H., Li, H., Wang, W., & Yao, T. (2014). A Sampling-based stochastic winner determination model for truckload service procurement. Networks and Spatial Economics. https://doi.org/10.1007/s11067-013-9214-6

    Article  Google Scholar 

  • Zhang, B., Yao, T., Friesz, T. L., & Sun, Y. (2015). A tractable two-stage robust winner determination model for truckload service procurement via combinatorial auctions. Transportation Research Part b: Methodological. https://doi.org/10.1016/j.trb.2015.03.019

    Article  Google Scholar 

  • Zhang, M., & Hu, Q. (2019). An effective evolutionary algorithm for the biobjective full truckload transportation service procurement problem. Computers and Industrial Engineering. https://doi.org/10.1016/j.cie.2018.11.036

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Iran University of Science and Technology, Tehran, Iran

    Aghdas Badiee & Hamed Kalantari

  2. University of Kent, Canterbury Kent, UK

    Chefi Triki

Authors
  1. Aghdas Badiee
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Hamed Kalantari
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Chefi Triki
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Hamed Kalantari.

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.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Badiee, A., Kalantari, H. & Triki, C. Leader-based diffusion optimization model in transportation service procurement under heterogeneous drivers’ collaboration networks. Ann Oper Res 322, 345–383 (2023). https://doi.org/10.1007/s10479-022-05029-z

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10479-022-05029-z

Keywords

Search

Navigation