## 1 Introduction  
In the airport field, the need to offer an efficient transport system is leading to a constant increase in the quality and safety of the service offered. In view of the growing demand for air transport in recent years, more attention should be paid to the qualitative conditions of the pavement, as it often involves the planning of repairs and restorations. Furthermore, various expansions and adaptations to the flight infrastructures are requested, to adapt them to the passage of higher category aircrafts [1]. In this context, the development of the airport pavement management system (APMS) is strategic, as it helps airport stakeholders to better manage all the airport infrastructures. In fact, applying an effective maintenance plan, a reduction of the life cycle cost, an increase in the service life and a maintenance of a high level of serviceability over the years is possible [2]. To function properly, the APMS has to be able to perform a series of operations [3] including the following macro-components: (I) the database, to collect and storage the data relating to the infrastructures under study; (II) the models, to allow the evaluation of the pavement condition; and (III) the analysis tools, to estimate the future pavement condition and select the optimal maintenance and rehabilitation (M&R) activities to be applied to the critical areas according to the adopted strategy. Since most of the studies relating to the pavement management system concern the road sector, various similarities have been exploited and appropriately calibrated in the research on the airport field. Usually, the optimization processes of the road pavement maintenance programs focus on factors such as limited resources, local climate, type of road classification and political considerations [4; 5; 6; 7]. In the airport field, further factorsare analyzed, namely the high operational impacts caused by the implementation of M&R activities. Hence, the APMS helps the airport managers to identify the most appropriate cost-effective activities, also evaluating the operational impact in a simple and intuitive way [8]. Obviously, every possible strategy has to comply with the requirements and rules of the current national and international legislation [9]. Usually, the strategies adopted could refer to routine, periodic or emergency maintenance [10]. In an emergency scenario, the pavement reaches the point of collapse, risking the stop of airport operations. The preventive activities, instead, are planned, so they allow maintenance of adequate conditions of the pavement with less invasive activities, minimizing the impact of airport operations. In any case, according to the strategy applied, possible factors triggering the activation of the different pavement repair type change, such as overall condition level, type of distress present, and rate of deterioration [11]. Based on the assumption that even small distresses to parts of the airport infrastructures can seriously compromise the functionality of their operations [12], correctly predicting the performance of the pavement through an accurate and efficient pavement deterioration model is the key element for the correct use of an APMS [13]. In fact, the selection and use of technical parameters and performance indicators lead to an accurate evaluation of pavement condition [14] and this choice has to be made carefully as it could influence subsequent M&R activities that are conducted. In this framework, the present research aims at analyzing how the strategies applied by airport managers influence the maintenance activities to be applied. In detail, the present approach includes both a clustering process, to minimize the fixed operating costs of the activities, and an optimization method or the choice of activities. Based on the previous knowledge submitted in the previous study by [PERSON] et al. [15], this work focuses on the influence factors that clustering and optimization processes have on APMS problems.