Pavement maintenance programming considering two objectives: maintenance costs and user costs
S Meneses, A Ferreira - International Journal of Pavement …, 2013 - Taylor & Francis
International Journal of Pavement Engineering, 2013•Taylor & Francis
This paper presents the development and implementation of a Multi-Objective Decision-Aid
Tool (MODAT) tested with data from the Estradas de Portugal's Pavement Management
System. The MODAT uses a multi-objective deterministic section-linked optimisation model
with different possible goals: minimisation of agency costs, minimisation of user costs,
maximisation of the residual value of pavements, etc. The MODAT also uses the
deterministic pavement performance model used in the AASHTO flexible pavement design …
Tool (MODAT) tested with data from the Estradas de Portugal's Pavement Management
System. The MODAT uses a multi-objective deterministic section-linked optimisation model
with different possible goals: minimisation of agency costs, minimisation of user costs,
maximisation of the residual value of pavements, etc. The MODAT also uses the
deterministic pavement performance model used in the AASHTO flexible pavement design …
This paper presents the development and implementation of a Multi-Objective Decision-Aid Tool (MODAT) tested with data from the Estradas de Portugal's Pavement Management System. The MODAT uses a multi-objective deterministic section-linked optimisation model with different possible goals: minimisation of agency costs, minimisation of user costs, maximisation of the residual value of pavements, etc. The MODAT also uses the deterministic pavement performance model used in the AASHTO flexible pavement design method. The application of the new Decision-Aid Tool is illustrated with a case study involving the main road network of Castelo Branco, a district of Portugal. In this application, the Knee point, that represents the most interesting solution of the Pareto frontier, corresponds to an agency costs weight value of 4% and an user costs weight value of 96%, demonstrating that user costs, which are generally much higher than agency costs, dominate the decision process.
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