A Limited Parking Space Scheduling Algorithm with Reservation

He Liangkun; Teng Shaohua; Zhang Wei

doi:10.12052/gdutxb.240126

English Version Journal Login

您当前的位置：

首页 >

文章列表页 >

A Limited Parking Space Scheduling Algorithm with Reservation

更新时间：2026-05-27

- A Limited Parking Space Scheduling Algorithm with Reservation
- Vol. 42, Issue 6, Pages: 44-51(2025)
- 作者机构：
  
  广东工业大学计算机学院,广东,广州,510006
- 作者简介：
- 基金信息：
- DOI：10.12052/gdutxb.240126
  CLC： TP311
- Published：2025
- 稿件说明：
移动端阅览
何亮昆, 滕少华, 张巍. 带预约的有限停车位调度算法[J]. 广东工业大学学报, 2025, 42(6): 44–51.

He Liangkun, Teng Shaohua, Zhang Wei. A Limited Parking Space Scheduling Algorithm with Reservation[J]. 2025, 42(6): 44-51.
何亮昆, 滕少华, 张巍. 带预约的有限停车位调度算法[J]. 广东工业大学学报, 2025, 42(6): 44–51. DOI： 10.12052/gdutxb.240126

He Liangkun, Teng Shaohua, Zhang Wei. A Limited Parking Space Scheduling Algorithm with Reservation[J]. 2025, 42(6): 44-51. DOI： 10.12052/gdutxb.240126.

摘要

停车场中常常会存在停车空位有时较少、有时较多的现象。停车场管理者的诉求是在时间一定的条件下，尽可能出租更多的车位和更长的停车时长，以获取更高的收益。然而，停车位调度存在两个问题。第一，现有调度方法忽略了对预约用户进行组合指派以获取当前收益最优的指派方案。第二，现有调度方法未能对停车资源进行整合优化以提高潜在收益。为了解决这些问题，本文提出了一种基于组合分配的停车位调度方法。首先，将预约订单看作代理，停车空位看作角色，以12 h作为一个调度周期。其次，在一个调度周期内，将代理进行组合并将组合代理作为指派元素，以避免订单被分散指派而导致资源的低效利用。接着，计算组合代理对角色的评估值，并约束停车费用越高的订单组合评估值越高，费用相同则间隔时间段数越少评估值越高。通过这种方式，能够保证在获取当前最优收益的同时，减少间隔时间段的数量以对停车资源进行整体调度。最后，以获取最大评估值为目标对组合代理进行指派。实验证明了所提方法的可行性，能够有效减少间隔时间段的数量并获得当前收益最优的指派方案。

Abstract

The number of available parking spaces is sometimes fewer

sometimes more. Managers aim to rent out as many parking spaces as possible within a certain time to maximize revenue. However

there are two problems in parking spaces scheduling. Firstly

existing methods overlook the combination assignment of reservation users to obtain the optimal assignment scheme. Secondly

existing scheduling methods fail to optimize parking resources to maximize the potential revenue. To solve these problems

this paper proposes a parking space scheduling method based on combinatorial allocation. Firstly

within a 12-hour scheduling cycle

orders and parking spaces are viewed as agents and roles

respectively. Secondly

multiple orders are formed into a combined agent. The combined agent is viewed as assignment elements to prevent inefficient resource utilization caused by the scattered order assignments. Then

evaluation values of combined agents for roles are calculated

with higher parking fees leading to higher values. For combined agents with the same fees

fewer time intervals result in higher evaluation values. By this way

the number of interval time periods can be reduced while obtaining the current optimal benefit. Finally

the combined agents are assigned with the objective of obtaining the maximum qualification values. Simulation experiments verify that the proposed method can reduce the number of parking interval time periods and obtain the assignment scheme with the best profit.

关键词

Keywords

references

ZHANG X Y, PITERA K, WANG Y Q. Parking reservation techniques: a review of research topics, considerations, and optimization methods[J]. Journal of Traffic and Transportation Engineering, 2023, 10(6): 1099-1117.

ABDEEN M A R, NEMER I A, SHELTAMI T R. A balanced algorithm for in-city parking allocation: a case study of Al Madinah City[J]. Sensors, 2021, 21(9): 3148.

WANG Y, CHEN Q. Dynamic parking allocation model in a multidestination multiple parking lot system[J]. IEEE Intelligent Transportation Systems Magazine, 2022, 14(5): 195-208.

NAKAZATO T, FUJIMAKI Y, NAMERIKAWA T. Parking lot allocation using rematching and dynamic parking fee design[J]. IEEE Transactions on Control of Network Systems, 2022, 9(4): 1692-1703.

YANG G, CHEN J, LU K, et al . Improving utilization efficiency and drivers’ degree of satisfaction in urban complex parking lot through modelling the dynamic allocation of parking spaces[J ] . Applied Sciences, 2021, 11(18): 8680-8696.

ZHANG W, LI W D, TENG S H, et al . A new insight in medical resources scheduling of physical examination with adaptive collaboration[C ] //2021 IEEE 24th International Conference on Computer Supported Cooperative Work in Design (CSCWD) . Dalian: IEEE, 2021: 546-551.

HUANG B Y, ZHU H B, LIU D N, et al . Solving last-mile logistics problem in spatiotemporal crowdsourcing via role awareness with adaptive clustering[J ] . IEEE Transactions on Computational Social Systems, 2021, 8(3): 668-681.

JIANG Q, ZHU H B, QIAO Y, et al . Refugee resettlement by extending group multirole assignment[J ] . IEEE Transactions on Computational Social Systems, 2021, 10(1): 36-47.

CHENG Z X, ZHU H B, LIU D N. Solving the external auditor assignment problem via GMRACCF[C]//2024 27th International Conference on Computer Supported Cooperative Work in Design (CSCWD) . Tianjin: IEEE, 2024: 1479-1484.

LIU X F, ZHU H B, LIU D N. Solving the energy supply strategic planning problem by extended group multirole assignment[C]//2024 27th International Conference on Computer Supported Cooperative Work in Design (CSCWD) . Tianjin: IEEE, 2024: 1461-1466.

KE X T, ZHU H B, LIU D N. Group multirole assignment with cooperation, conflict, and public interest factors[J]. IEEE Transactions on Computational Social Systems, 2024, 11(5): 6112-6124.

REN J X, CHANG X. A shared parking allocation model based on customer satisfaction[J]. Mathematics in Practice and Theory, 2024, 54(9): 38-51.

KIM O T, TRAN N H, PHAM C, et al . Parking assignment: Minimizing parking expenses and balancing parking demand among multiple parking lots[J ] . IEEE Transactions on Automation Science and Engineering, 2019, 17(3): 1320-1331.

WANG Y Q, LIN S Y, XIE M H, et al . Dynamic reservation and allocation optimization model of shared parking slots in multiple parking lots[J ] . Journal of South China University of Technology(Natural Science Edition) , 2022, 50(9): 12-21.

JIANG Q, LIU D N, ZHU H B, et al . Quasi group role assignment with role awareness in self-service spatiotemporal crowdsourcing[J ] . IEEE Transactions on Computational Social Systems, 2022, 9(5): 1456-1468.

LIANG L, FU J D, ZHU H B, et al . Solving the team allocation problem in crowdsourcing via group multirole assignment[J ] . IEEE Transactions on Computational Social Systems, 2022, 10(3): 843-854.

MA H, LI J Z, ZHU H B, et al . Collaborative optimization of learning team formation based on multidimensional characteristics and constraints modeling: a team leader-centered approach via E-CARGO[J ] . IEEE Transactions on Computational Social Systems, 2022, 11(1): 184-196.

ZHU H B. Group role assignment with constraints (GRA+): a new category of assignment problems[J]. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2022, 53(3): 1670-1683.

TENG S H, CHEN Y H, TENG L Y, et al . Solving injection molding production cost problem based on combined group role assignment with costs[C ] //International Conference on Web Information Systems Engineering. Singapore: Nature, 2023: 748-762.

Views

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Group Role Assignment Based on KD45 Closure

Multiple Assignment in Task Allocation of Communication Base Stations

Bidding Prediction of Advertisement Keywords via Group Role Combination

Efficient Temporal Modeling for RGB-T Tracking

An Optimal Operation Strategy for Community Microgrid Alliances Considering Power Exchange under Multi-package Shared Energy Storage Model

Related Author

Zhang Wei

Tong Ru

Wu Shi-jue

Wang Zi-qi

Teng Shao-hua

Liu Dong-ning

Liu Tong-wu

Song Jing-jing

Related Institution

School of Computers, Guangdong University of Technology

Guangdong Provincial Audit Office

College of Civil Engineering, Shenzhen University

AI问答

⁰