Maintenance and improvement, through the rehabilitation, of the road infrastructure is a strategic and priority objective for road agencies, nevertheless the economic resources required are often inadequate. Within road management, the pavement management system (PMS) plays an essential role because of both the money needed and the performance that should be provided in terms of safety, ride quality and transport cost. The PMS is based on searching for a balanced solution between the lowest cost and the increased level of performance (i.e. pavement condition). In this paper a PMS multi-objective optimization method, was proposed, using a genetic algorithm (GA) to identify the best solution considering different rehabilitation strategies. The multi-objective optimization GA permits a set of optimal solutions (the Pareto solution set) that takes into account all the considered constraints. Finally on the basis of a specific criteria the best solution was selected in relation to the ranking of the priorities of the agency. A detailed numerical study was conducted on the Italian A18 motorway and the results showed that the proposed model PMS-GA is a suitable support to the decision making process.

Di Mino, G., De Blasiis, M.R., Di Noto, F., Noto, S. (2013). An Advanced Pavement Management System based on a Genetic Algorithm for a Motorway Network. In CSC2013-S06 Soft Computing Applications in Transportation Engineering.

An Advanced Pavement Management System based on a Genetic Algorithm for a Motorway Network

DI MINO, Gaetano;NOTO, Silvia
2013-01-01

Abstract

Maintenance and improvement, through the rehabilitation, of the road infrastructure is a strategic and priority objective for road agencies, nevertheless the economic resources required are often inadequate. Within road management, the pavement management system (PMS) plays an essential role because of both the money needed and the performance that should be provided in terms of safety, ride quality and transport cost. The PMS is based on searching for a balanced solution between the lowest cost and the increased level of performance (i.e. pavement condition). In this paper a PMS multi-objective optimization method, was proposed, using a genetic algorithm (GA) to identify the best solution considering different rehabilitation strategies. The multi-objective optimization GA permits a set of optimal solutions (the Pareto solution set) that takes into account all the considered constraints. Finally on the basis of a specific criteria the best solution was selected in relation to the ranking of the priorities of the agency. A detailed numerical study was conducted on the Italian A18 motorway and the results showed that the proposed model PMS-GA is a suitable support to the decision making process.
Settore ICAR/04 - Strade, Ferrovie Ed Aeroporti
set-2013
Third International Conference on Soft Computing Technology in Civil, Structural and Environmental Engineering
cagliari Italy
3-6 September 2013
2013
17
Di Mino, G., De Blasiis, M.R., Di Noto, F., Noto, S. (2013). An Advanced Pavement Management System based on a Genetic Algorithm for a Motorway Network. In CSC2013-S06 Soft Computing Applications in Transportation Engineering.
Proceedings (atti dei congressi)
Di Mino, G; De Blasiis, MR; Di Noto, F; Noto, S
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10447/102612
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