考虑匹配优先级的共享混合停车位租用与分配问题研究

为充分利用混合停车场的停车和充电资源，本文依据出行者需求的差异性设置匹配优先级，在此基础上以共享平台接受并出租车位的收益扣除拒绝请求的惩罚成本的总收益最大化为目标，以充电量不超过停车场负荷为约束条件，建立考虑匹配优先级的共享混合停车位租用与分 配(MPRA)模型。基于匹配优先级原则和模型特征改进蚁群算法，设置分块冲突矩阵，根据分块冲突矩阵设计蚂蚁信息素更新策略和路径选择策略并进行求解。最后算例证实了考虑匹配优先级的必要性，并分析了问题规模对MPRA分配方案的影响。研究结果表明：在充电需求匹配率方面，MPRA方案高于利润最大化方案，平均提升率为28.96%，这一优势与出行者数量或车位数量成反比，且利润提升率随着问题规模的增加而增加；车位数量有限时，MPRA方案相较于先到先停方案可以极大化提升车位利用率和充电需求匹配率，平均提升率分别为17.87%和113.96%。

Rental and Allocation of Shared Mixed Parking Spaces Considering Matching Priority

This paper establishes the matching priority based on travelers' demands and in full consideration of the parking and charging resources of mixed parking spaces. A shared parking space rental and allocation model with matching priority (MPRA) is developed to maximize the total income of the shared platform, deducting the penalty cost for rejecting parking requests from rental incomes, with the constraint that the charging amount does not exceed the parking lot load. Based on the matching priority principle and model characteristics, the study proposes the improved ant colony algorithm by introducing a block conflict matrix and the pheromone update strategy. The numerical examples imply the matching priority and the effect of problem scales on MPRA allocation scheme. The results show that the proposed MPRA scheme results in higher charging demand matching rate than the profit maximization scheme, the average improvement rate is 28.96%. This advantage is inversely proportional to the number of travelers or spaces, and the profit improvement rate increases with the increase of the problem size. When the number of parking spaces is scarce, the MPRA scheme can improve the parking utilization rate by 17.87% and improve the charging demand matching rate by 113.96% compared to the first-come-first-serve scheme.