- Tytuł:
- Flow-capture location model with link capacity constraint over a mixed traffic network
- Autorzy:
-
Liu, Ping
Cao, Jinde
Luo, Yiping
Guo, Jianhua
Huang, Wei - Powiązania:
- https://bibliotekanauki.pl/articles/2147143.pdf
- Data publikacji:
- 2022
- Wydawca:
- Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
- Tematy:
-
traffic assignment problem
link capacity constraint
charging location
pathmdistance constraint - Opis:
- 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.
- Źródło:
-
Journal of Artificial Intelligence and Soft Computing Research; 2022, 12, 3; 223--234
2083-2567
2449-6499 - Pojawia się w:
- Journal of Artificial Intelligence and Soft Computing Research
- Dostawca treści:
- Biblioteka Nauki
Artykuł