Research on Vehicle and Goods Matching Optimization and Recommendation Model of Network Freight Platform

DOI

10.2991/978-94-6463-570-6_121How to use a DOI?

Keywords

car-goods matching; intuitive fuzzy rough set; prospect theory; multi-attribute fuzzy decision

Abstract

Network freight platforms face the complex task of truck-goods matching, which involves considering user conditions and demands. The matching process evaluates ten indicators, such as vehicle type and reputation, using intuitionistic fuzzy rough sets to represent scores and degrees of satisfaction, dissatisfaction, and hesitation. An optimization model based on prospect theory, with the zero point as a reference, maximizes the comprehensive foreground value. A multi-attribute fuzzy decision model is constructed to optimize overall satisfaction, transforming intuitionistic unclear data into a decision matrix and comparing distances to ideal and negative ideal schemes for ranking. Experimental data from a freight platform shows that the algorithm achieves the highest recommendation accuracy when handling 100 users and 20 items, increasing matching satisfaction by 13.8% over traditional collaborative filtering methods. The algorithm maintains the lowest average absolute error (MAE) value of 0.536, boosting the accuracy rate by 23.4%, and offers effective decision support for improving matching efficiency and recommendation satisfaction on the platform.

Copyright

© 2024 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Yanju Zhang
AU  - Yixuan Wu
AU  - Lu Ma
PY  - 2024
DA  - 2024/11/22
TI  - Research on Vehicle and Goods Matching Optimization and Recommendation Model of Network Freight Platform
BT  - Proceedings of the 2024 5th International Conference on Management Science and Engineering Management (ICMSEM 2024)
PB  - Atlantis Press
SP  - 1211
EP  - 1220
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6463-570-6_121
DO  - 10.2991/978-94-6463-570-6_121
ID  - Zhang2024
ER  -