Exploring New Computational Strategies for Managing Maintenance Activities of Airport Pavement Systems

In this paper, the optimization of the maintenance management problem regarding airport pavements is addressed by developing a series of fast computational procedures whose rationales pursue both practical and economical objectives. Particularly, the study involves the design of five new heuristic algorithms replicating different management strategies that can be undertaken by the airport managers in a certain time horizon for reducing the pavement maintenance costs while considering the impact on the service level of the airport. Each algorithm works on the basis of a preliminary computational framework that has a twofold scope: (i) selecting the pavement portions to be maintained during the provided time horizon. (ii) using a K-means method based on three well-known performance indicators, which, namely, are Residual Life (RL), International Roughness Index (IRI) and Pavement Condition Index (PCI), to group the selected portions into homogenous clusters named work-zones. To evaluate the effectiveness and the efficiency of the proposed optimization algorithms in coping with the maintenance programming problem under investigation, an extended design of experiments based on international airport regulations has been arranged. The obtained numerical results revealed that no single strategy can be selected as the most performing in terms of cost and quality conditions of the pavements. To make robust the numerical results, a sensitivity analysis is conducted to evaluate the influence of the total cost of maintenance on runway length and number of sections. However, the results obtained in this study provide a series of managerial implications, further expanding the research contribution.