薛召杰,袁秋芳,季楷丰.基于缓冲时间的共享车位分配鲁棒方法[J].深圳大学学报理工版,2022,39(02):216-222.[doi:10.3724/SP.J.1249.2022.02216] XUE Zhaojie,YUAN Qiufang,and JI Kaifeng.Robust method of shared parking allocation based on buffer time[J].Journal of Shenzhen University Science and Engineering,2022,39(02):216-222.[doi:10.3724/SP.J.1249.2022.02216]
Robust method of shared parking allocation based on buffer time
XUE Zhaojie1,2,3,YUAN Qiufang1,and JI Kaifeng4,5
1.College of Civil and Transportation Engineering, Shenzhen University, Shenzhen 518061, Guangdong Province, P. R. China;2.Key Laboratory of Coastal Urban Resilient Infrastructures of Ministry of Education, Shenzhen University, Shenzhen 518061, Guangdong Province, P. R. China;3.Underground Polis Academy, Shenzhen University, Shenzhen 518061, Guangdong Province, P. R. China;4.Shenzhen Qianhai Smart Transportation Operation&Technology Co. Ltd., Shenzhen 518052, Guangdong Province, P. R. China
Shared parking platform determines the parking allocation schemes according to the time windows of parking supplies and parking demands. In order to deal with uncertain situations such as early arrival or delayed departure during parking, the robustness of the parking allocation scheme is enhanced by reserving appropriate buffer time. This paper builds a bi-objective optimization model of parking space allocation problem that maximizes the platform revenue and the robustness. The bi-objective function is transformed into a single objective function by the weighted sum method, and the nonlinear model is transformed into a linear model by adding auxiliary decision variables. Finally, the effectiveness of the method is verified by a numerical example, and the sensitivity analysis of key parameters is carried out. The results show that within a reasonable time, the method can obtain the optimal solution and various index values of the example. With the increase of the dual-objective adjustment coefficient, the platform revenue segment increases, while the robustness segment decreases. The non-dominated solutions are screened out from the optimal solutions obtained by different adjustment coefficients, and the approximate Pareto frontier curve is obtained by fitting. The robustness reduction varies in the range of [0.02, 6.75].
[5]孙会君,傅丹华,吕 莹,等.基于共享停车的车位租用与分配模型[J].交通运输系统工程与信息, 2020,20(3):130-136. SUN Huijun, FU Danhua, LV Ying, et al. Parking spaces renting and allocation model for shared parking [J]. Jour‐nal of Transportation Systems Engineering and Information Technology, 2020, 20(3): 130-136. (in Chinese)
[6]张水潮,蔡逸飞,黄 锐,等.基于预约需求的共享停车平台泊位分配方法[J].交通运输系统工程与信息,2020,20(3):137-143,162. ZHANG Shuichao, CAI Yifei, HUANG Rui, et al. Shared parking space allocation method considering reservation demand [J]. Journal of Transportation Systems Engineering and Information Technology, 2020, 20(3): 137-143, 162. (in Chinese)