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A network flow model for clustering segments and minimizing total maintenance and rehabilitation cost

机译:一种网络流量模型,用于对网段进行聚类并最大程度地减少总维护和修复成本

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摘要

Because of shrinking budgets, transportation agencies are facing severe challenges in the preservation of deteriorating pavements. There is an urgent need to develop a methodology that minimizes maintenance and rehabilitation (M&R) cost. To minimize total network M&R cost of clustering pavement segments, we propose an integer programming model similar to an uncapacitated facility location problem (UFLP) that clusters pavement segments contiguously. Based on the properties of contiguous clustered pavement segments, we have transformed the clustering problem into an equivalent network flow problem in which each possible clustering corresponds to a path in the proposed acyclic network model. Our proposed shortest-path algorithm gives an optimal clustering of segments that can be calculated in a time polynomial to the number of segments. Computational experiments indicate our proposed network model and algorithm can efficiently deal with real-world spatial clustering problems.
机译:由于预算减少,运输机构在保护恶化的人行道方面面临严峻挑战。迫切需要开发一种使维护和修复(M&R)成本最小化的方法。为了使聚集路段的总网络M&R成本最小化,我们提出了一个整数规划模型,该模型类似于连续聚集路段的无能力设施位置问题(UFLP)。基于连续的聚类的人行道路段的性质,我们已将聚类问题转换为等效的网络流量问题,其中每个可能的聚类都对应于所提出的非循环网络模型中的路径。我们提出的最短路径算法提供了段的最佳聚类,可以在时间多项式中计算段的数量。计算实验表明,我们提出的网络模型和算法可以有效处理现实世界中的空间聚类问题。

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