@article{ref1,
title="A mixed decision strategy for freight and passenger transportation in metro systems",
journal="Computational intelligence and neuroscience",
year="2021",
author="Guo, Junhua and Ye, Yutao and Yan, Lixin",
volume="2021",
number="",
pages="e5412016-e5412016",
abstract="This paper proposes a mixed decision strategy for freight and passenger transportation in metro systems during off-peak hours (MTS-OPH). The definition of the mixed decision strategy is proposed, and fixed and flexible loading modes are considered for different passenger flow volumes. A mathematical model of the MTS-OPH is proposed and solved using an improved variable neighborhood search algorithm. Case studies demonstrate the performance and applicability of the proposed model and algorithm, and the MTS-OPH is discussed for different delivery distances, passenger flows, and metro network types. The proposed strategy is suitable for long-distance delivery, and the proposed model framework can be applied to different types of metro networks with different levels of complexity. The mixed decision strategy provides a decision support tool for metro and freight companies and can propose corresponding solutions according to different passenger flows.<p /> <p>Language: en</p>",
language="en",
issn="1687-5265",
doi="10.1155/2021/5412016",
url="http://dx.doi.org/10.1155/2021/5412016"
}