Research on vehicle-cargo matching algorithm considering price heterogeneity

Xuliang Sun; Daning Xing

doi:10.1117/12.3051307

20 January 2025 Research on vehicle-cargo matching algorithm considering price heterogeneity

Xuliang Sun, Daning Xing

Author Affiliations +

Proceedings Volume 13422, Fourth International Conference on Intelligent Traffic Systems and Smart City (ITSSC 2024); 134220H (2025) https://doi.org/10.1117/12.3051307
Event: Fourth International Conference on Intelligent Traffic Systems and Smart City (ITSSC 2024), 2024, Xi'an, China

Abstract

To enhance the efficiency of vehicle-cargo matching on the platform, this study delves into the issue of price heterogeneity alongside previous research on matching rates, transportation costs, and more. Addressing this problem, this study constructs a multi-objective optimization model aimed at maximizes the overall satisfaction of vehicle owners, cargo owners, and platform profits. An improved dynamic Bayesian network (IDBN) combined with a fast non-dominated sorting genetic algorithm with an elite retention strategy (NSGA-II) is proposed for vehicle-cargo matching. Firstly, the fuzzy analytic hierarchy process is employed to calculate the vehicle-cargo matching degree hierarchically. Secondly, a dynamic Bayesian network structure is constructed, mapping vehicles, cargoes, and matching combinations to Bayesian network nodes, and solving the multi-objective model for more practical results. The algorithm is compared with the IDBN algorithm in the experimental process. Results reveal that the proposed algorithm enhances the average satisfaction by 90.87% and increases platform profits by an average of 235.60 yuan per time slice, demonstrating its feasibility on the platform.

(2025) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Xuliang Sun and Daning Xing "Research on vehicle-cargo matching algorithm considering price heterogeneity", Proc. SPIE 13422, Fourth International Conference on Intelligent Traffic Systems and Smart City (ITSSC 2024), 134220H (20 January 2025); https://doi.org/10.1117/12.3051307

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