优化的集中式动态路边停车位分区
Optimal, centralized dynamic curbside parking space zoning
摘要：
在本文中，我们制定了一个动态的混合整数规划的最佳分区路边停车位的交通政策启发的约束和正则化条款。首先，我们说明了如何给定一些目标的遏制分区估价作为一个功能的区域类型（例如，付费停车场或公共汽车站），动态重新分区涉及在固定时间范围内展开该优化程序。其次，我们实现了两种不同的解决方案的方法，优化一个给定的遏制分区值函数。在第一种方法中，我们用近似动态规划来求解长时间动态分区问题。在第二种方法中，我们采用Dantzig-Wolfe分解成一个主问题和几个子问题，我们并行解决的混合整数规划，这种分解大大加快了MIP求解器。我们目前的模拟结果和比较不同的车辆到达率数据在西雅图市中心，华盛顿州，美国的一个社区所采用的技术
英文摘要：
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
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