Proceedings of the 3rd International Conference on Advances in Management Science and Engineering (IC-AMSE 2020)

Vehicle-Cargo Matching Optimization Model for Vehicle Capacity Scheduling Platform

Authors
Qingying Zhang
Corresponding Author
Qingying Zhang
Available Online 6 April 2020.
DOI
https://doi.org/10.2991/aebmr.k.200402.046How to use a DOI?
Keywords
highway transportation, vehicle-cargo matching, multi-objective optimization, capacity scheduling, time window
Abstract
In this paper, the problem of imbalance in the organization of freight resources in the platform is studied. From the perspective of the platform, a freight resource selection model with the constraint of cargo source urgency is established. The advantage of this model lies in that it comprehensively considers the three important influencing factors including the interests of all parties, the urgency of cargo sources and the effective utilization rate of freight resources. It can realize the optimization scheme of freight resources selection under multiple constraints and improve the effective utilization rate of car-free carrier resources. At the same time, the effect of freight transaction conversion rate is promoted. Through the analysis of calculation examples, it is proved that the model proposed in this paper can meet the demand of time window of goods source. Compared with the multi-objective sequencing and matching method, the model proposed in this paper can improve the effective utilization rate of the platform’s transport capacity resources.
Open Access
This is an open access article distributed under the CC BY-NC license.

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Cite this article

TY  - CONF
AU  - Qingying Zhang
PY  - 2020
DA  - 2020/04/06
TI  - Vehicle-Cargo Matching Optimization Model for Vehicle Capacity Scheduling Platform
BT  - Proceedings of the 3rd International Conference on Advances in Management Science and Engineering (IC-AMSE 2020)
PB  - Atlantis Press
SP  - 260
EP  - 267
SN  - 2352-5428
UR  - https://doi.org/10.2991/aebmr.k.200402.046
DO  - https://doi.org/10.2991/aebmr.k.200402.046
ID  - Zhang2020
ER  -