论文标题
最佳，集中的动态路边停车位分区
Optimal, centralized dynamic curbside parking space zoning
论文作者
论文摘要
在本文中，我们制定了一个动态混合整数程序，用于最佳分区路缘停车位，受到运输政策启发的约束和正则化项的约束。首先，我们说明如何将分区估值作为区域类型的函数（例如，付费停车或公交站）的函数进行一些目标，动态重新分区涉及在固定的时间范围内展开此优化程序。其次，我们实施了两种不同的解决方案方法，可针对给定的路缘分区值函数进行优化。在第一种方法中，我们通过近似动态编程解决了长时间的地平线动态分区问题。在第二种方法中，我们采用Dantzig-Wolfe的分解将混合成员程序分解为主问题，并并行解决了几个子问题。这种分解大大加速了MIP求解器。我们提出了有关在美国华盛顿州西雅图市中心获得的车辆到达率数据的不同采用技术的模拟结果和比较
In this paper we formulate a dynamic mixed integer program for optimally zoning curbside parking spaces subject to transportation policy-inspired constraints and regularization terms. First, we illustrate how given some objective of curb zoning valuation as a function of zone type (e.g., paid parking or bus stop), dynamically rezoning involves unrolling this optimization program over a fixed time horizon. Second, we implement two different solution methods that optimize for a given curb zoning value function. In the first method, we solve long horizon dynamic zoning problems via approximate dynamic programming. In the second method, we employ Dantzig-Wolfe decomposition to break-up the mixed-integer program into a master problem and several sub-problems that we solve in parallel; this decomposition accelerates the MIP solver considerably. We present simulation results and comparisons of the different employed techniques on vehicle arrival-rate data obtained for a neighborhood in downtown Seattle, Washington, USA
