Abstract
ABSTRACT An airport pavement management system is of great significance in terms of allocating budget and resources as well as preserving the level of serviceability and safety. In order to provide a more accurate, reliable, and applicable plan for airport pavement management, the combination and interrelation of four crucial affecting factors should be considered: pavement age, traffic load frequency, weather conditions, as well as maintenance actions effects. These factors have not been comprehensively studied enough neither within the deterioration modelling, which is the core of airport pavement management, nor through the decision-making procedure. The Markov Chain method is used for deterioration modelling. The data required to build up Markov Chain deterioration models are collected through questionnaires filled by experts. Having built up deterioration models, the second version of Non-Dominated Sorting Genetic Algorithms (NSGA-II) is applied to solve pavement management problems, i.e. providing a pavement maintenance activity plan over the planning horizon through a supervised manner considering both pavement conditions and monetary resources as objective functions. Finally, the proposed plan maintains a minimum acceptable level of airport pavement conditions over the planning horizon minimizing budget.
Published Version
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