Optimal Pavement Maintenance Programs Based on a Hybrid Greedy Randomized Adaptive Search Procedure Algorithm

Abstract

Abstract. Insufficient investment in the public sector together with inefficient maintenance infrastructure programs lead to high economic costs in the long term. Thus, infrastructure managers need practical tools to maximize the Long-Term Effectiveness (LTE) of maintenance programs. This paper describes an optimization tool based on a hybrid Greedy Randomized Adaptive Search Procedure (GRASP) considering Threshold Accepting (TA) with relaxed constraints. This tool facilitates the design of optimal maintenance programs subject to budgetary and technical restrictions, exploring the effect of different budgetary scenarios on the overall network condition. The optimization tool is applied to a case study demonstrating its efficiency to analyze real data. Optimized maintenance programs are shown to yield LTE 40% higher than the traditional programs based on a reactive strategy. To extend the results obtained in this case study, a set of simulated scenarios, based on the range of values found in the real example, are also optimized. This analysis concludes that this optimization algorithm enhances the allocation of maintenance funds over the one obtained under a traditional reactive strategy. The sensitivity analysis of a range of budgetary scenarios indicates that the funding level in the early years is a driving factor of the LTE of optimal maintenance programs.

State-of-the-Art Review on Sustainable Design and Construction of Quieter Pavements—Part 1: Traffic Noise Measurement and Abatement Techniques

“…However, FHWA [4] pointed out that there should be a striking balance between particular importance and feasibility. Therefore, it is necessary to perform a multi-criteria pavement analysis before adopting any noise abatement techniques [73][74][75]. Multi-criteria analysis includes number of factors such as technical feasibility, the unique characteristics of highway generated noise, cost, overall public interest, and aesthetic considerations that should be taken into account before choosing a noise abatement technique [4].…”

Optimization of Biclustering Algorithm Based on Greedy Randomized Adaptive Search Procedure

“…In this paper, a greedy randomized adaptive search procedure [18,19,20] is used to expand the bicluster seeds, which includes the construction phase [21,22] elements and greedy function values should be updated promptly to reflect their changes, which is the embodiment of the self-adaption function in the algorithm. The greedy function [7,8] in this paper is:…”

A fuzzy logic expert system for selecting optimal and sustainable life cycle maintenance and rehabilitation strategies for road pavements

“…It has promising characteristics that can help to tackle the challenges abovementioned (Santos et al 2018b). Different optimisation methods have been applied in the pavement management field for the design of M&R strategies, including: linear and non-linear programming (de la Garza et al 2011, Gao et al 2012), integer programming (Ferreira et al 2002, Ng et al 2011, dynamic programming , local search heuristics (Yepes et al 2016, Torres-Machi et al 2017, and evolutionary algorithms (Santos et al 2018a(Santos et al , 2019, among others (Torres-Machi et al 2014a). Although these methods differ on the mathematical approach used to solve the optimisation problem, they all seek the best M&R strategies that should be applied over the analysis period.…”