Intelligent planning of road pavement rehabilitation processes through optimization systems

Transportation Engineering

Manuel Parente¹  Ana Margarida Amândio²  José Manuel Coelho das Neves³ 

[1] Corresponding author.;BUILT CoLAB, Rua de Álvares Cabral 306, Porto 4050-040, Portugal;CERIS, Instituto Superior Técnico, Universidade de Lisboa, Avenida Rovisco Pais, Lisboa 1049-001, Portugal;

关键词: Artificial intelligence;    Pavement rehabilitation;    Optimization;    Project management;    Metaheuristics;   

DOI  :  

来源: DOAJ

【 摘 要 】

Pavement rehabilitation comprises a very time sensitive and complex set of operations. Not only does this type of construction typically rely on very expensive heavy mechanical equipment, it also usually involves closing lanes that will inevitably cause delays to users. Although there is an increasing interest in completing these rehabilitation interventions with the lowest costs and durations, the planning of this process is currently mostly based on experience. Thus, this paper focuses on developing an optimization system based on an evolutionary multi-objective approach, capable of supporting decision making in road pavement rehabilitation planning. The main contributions of this paper are two-fold. On the one hand, it tackles an identified research gap regarding the study of the viability and the gain associated with the implementation of multi-objective optimization in planning of pavement rehabilitation projects. On the other hand, a more practical contribution is related to the development of a system capable of supporting decision making throughout design phases. The capabilities of the system are validated in a real motorway pavement rehabilitation project. Results demonstrate the ability of the system to quickly output optimal solutions, that not only support decision making, but also enhance flexibility and efficiency from the decision-maker viewpoint. The optimization system is an important contribution to more intelligent and sustainable pavement engineering, by promoting the global optimization of technical, economic and environmental objectives.

【 授权许可】

Unknown