Flow-capture location model with link capacity constraint over a mixed traffic network

• Autorzy: Liu Ping , Cao Jinde , Luo Yiping , Guo Jianhua , Huang Wei

Identyfikatory

DOI

10.2478/jaiscr-2022-0015

• Języki publikacji: EN

Abstrakty

EN

This paper constructs and settles a charging facility location problem with the link capacity constraint over a mixed traffic network. The reason for studying this problem is that link capacity constraint is mostly insufficient or missing in the studies of traditional user equilibrium models, thereby resulting in the ambiguous of the definition of road traffic network status. Adding capacity constraints to the road network is a compromise to enhance the reality of the traditional equilibrium model. In this paper, we provide a two-layer model for evaluating the efficiency of the charging facilities under the condition of considering the link capacity constraint. The upper level model in the proposed bi-level model is a nonlinear integer programming formulation, which aims to maximize the captured link flows of the battery electric vehicles. Moreover, the lower level model is a typical traffic equilibrium assignment model except that it contains the link capacity constraint and driving distance constraint of the electric vehicles over the mixed road network. Based on the Frank-Wolfe algorithm, a modified algorithm framework is adopted for solving the constructed problem, and finally, a numerical example is presented to verify the proposed model and solution algorithm.

Słowa kluczowe

EN

traffic assignment problem; link capacity constraint; charging location; pathmdistance constraint

• Wydawca: University of Social Sciences
• Czasopismo: Journal of Artificial Intelligence and Soft Computing Research
• Rocznik: 2022
• Tom: Vol. 12, No. 3
• Strony: 223--234
• Opis fizyczny: Bibliogr. 27 poz., rys.

Twórcy

autor

Liu Ping

• School of Transportation, Southeast University, Nanjing 210096, China

autor

Cao Jinde

• School of Mathematics, Southeast University, Nanjing 210096, China
• Yonsei Frontier Lab, Yonsei University, Seoul 03722, South Korea

autor

Luo Yiping

• College of Electrical & Information Engineering, Hunan Institute of Engineering, Xiangtan City, Hunan Province, 411104, China

autor

Guo Jianhua

• School of Transportation, Southeast University, Nanjing 210096, China

autor

Huang Wei

• Intelligent Transportation System Research Center, Southeast University, Nanjing 210096, China

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