居住区共享泊位资源优化配置模型及算法

对于缓解城市停车难问题,基于泊位共享的理念充分挖掘现有私人或者专用停车位资源以供社会车辆停放的方法成为一种新的思路.由于共享车位可利用的停车时段通常具有严格的时间窗约束和片段化特征,导致共享车位资源在实际运营中难以得到高效利用.本文旨在通过设计优化配置算法,以提高共享泊位利用率为目标,将居住区泊位拥有者愿意出租的停车时段与停车需求进行匹配,从而实现共享车位的高效利用.首先,基于具有颜色约束的加权顶点着色问题,建立共享车位资源优化配置模型;其次,针对以上NP-C问题,分析蚁群算法的路径选择及信息素更新策略并设计求解算法;最后,根据居住区泊位空闲特性设计仿真实验,并与"先到先服务"的停车位资源配置方法对比,结果显示,本文提出的优化方法可以将泊位利用时长提高11.82%.

A Model and Algorithm for Optimization of the Utilization of Residential Shared Parking Slots

In order to solve the parking problems in major cities, an innovative method based on shared parking theory is proposed which aims at making the fullest use of the private-owned and non-public parking slots to satisfy the increasing parking demand. Since the time available for parking is often consists of discrete fragments, exerting rigid time restraints for parking, efficient utilization of those parking slots resources is hard to achieve in practice. An optimization method, focused on higher parking slots occupancy rate, is designed to match the available time intervals parking slots supply and the parking demand from drivers, thus realizing the efficient utilization of the shared parking slots. First, a model and formulation based on weighted vertex coloring problem with restrictions on colors is given which aims at making the fullest use of the parking slots; then a modified ACO (Ant Colony Optimization) algorithm is provided so as to solve the NP-C problem by specifying the strategies for route choosing and pheromone updating; finally experiments are conducted based on the features of the parking slots supply which make a comparison between the modified ACO algorithm and the FCFS (First Come First Serve) algorithm. The results of the experiments show the performance, characterized by the total amount of time allocated to the drivers, of modified ACO is 11.82% higher than the FCFS algorithm.