Affiliations: [a] School of Business Administration, Northeastern University, Shenyang, China
| [b] School of Economics and Management, Xinjiang University, Urumqi, China
Correspondence:
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Corresponding author. Zhenpeng Tang, School of Economics and Management, Xinjiang University, Urumqi, China. E-mail: tang.zp@outlook.com.
Abstract: There has been widespread and growing concern about parking. This paper attempts to provide decision support for a shared parking system to reduce parking difficulty. We study a many-to-many matching problem between shared private idle parking spaces and their demanders. A novelty is that the demanders are allowed to use different parking spaces successively in parking relocation service support. This can further reintegrate the idle time of the parking spaces and improve their utilization rate. A multi-objective optimization model is constructed to maximize the number of matched demanders, the total priority of the parking spaces, and the total priority of the demanders. More importantly, the priorities of the parking spaces and the demanders are innovatively considered. Each of the parking spaces and the demanders is given a priority for the matching and the priority of a parking space or a demander will be increased if the parking space or demander rarely gets matched successfully. This helps reduce the withdrawal of parking spaces and the demanders from the parking platform. In addition, an NSGA-II algorithm is designed to solve the model efficiently. Finally, the feasibility of the proposed method is illustrated via an example.
