ABSTRACT

A highway in poor conditions can raise transportation costs. Due to budgetary constraints, pavement maintenance programming is considered a difficult decision-making problem. In this article we propose a novel mathematical model and a different variant of the pavement maintenance management problem, solved with integer linear programming. The novelty of this approach is the use of the Pavement Surface Rating as the condition indicator, along with a proposed conversion strategy between most used performance indices. Additionally, we propose a simpler and broader deterioration model, when compared to existent ones, using a table system. This renders the model to be solved easily, allowing it to be implemented worldwide, given its generic characteristics. Many computational experiments were performed, both on artificial benchmark instances and on a real-world case study. The proposed model is shown to obtain optimal solutions in short computational times, and it is able to solve much larger instances than the ones found in the literature. Optimal solutions from benchmark instances, consisting of 5,000 segments and an analysis period of 30 years, were found in less than 45 minutes. Additionally, the optimal solutions have a difference of more than 20% in average, when compared to a greedy algorithm.

摘要

状况不佳的高速公路会增加运输成本。由于预算限制，路面养护计划被认为是一个困难的决策问题。在本文中，我们提出了一种新颖的数学模型和路面养护管理问题的另一种变体，并用整数线性规划法进行了求解。这种方法的新颖之处在于使用了路面表面等级作为状态指标，以及在大多数使用的性能指标之间提出的转换策略。此外，与现有模型相比，我们使用表格系统提出了一种更简单，更广泛的恶化模型。鉴于其通用特性，这使得该模型易于求解，可以在全球范围内实施。进行了许多计算实验，无论是在人工基准测试实例上还是在实际案例研究中。所提出的模型显示出可以在较短的计算时间内获得最佳解，并且它能够解决比文献中发现的更大的实例。在不到45分钟的时间内，发现了由5,000个细分组成的基准实例的最佳解决方案，分析期为30年。此外，与贪婪算法相比，最佳解决方案的平均差异超过20％。