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Applied Metaheuristic Optimization in Asphalt Pavement Management
Author(s) -
Luis Ricardo Vásquez-Varela,
Francisco Javier García-Orozco
Publication year - 2021
Publication title -
ciencia e ingeniería neogranadina
Language(s) - English
Resource type - Journals
eISSN - 1909-7735
pISSN - 0124-8170
DOI - 10.18359/rcin.4371
Subject(s) - pavement management , metaheuristic , pavement engineering , computer science , asphalt pavement , reliability (semiconductor) , transport engineering , engineering , asphalt , power (physics) , artificial intelligence , physics , cartography , quantum mechanics , geography
Pavement engineering is a crossroads between geotechnical and transportation engineering with a sound base on construction materials. There are multiple applications of optimization algorithms in pavement engineering, emphasizing pavement management for its socioeconomic implications and back-calculation of layer properties for its complexity. A detailed literature review shows that optimization has been a permanent concern in pavement engineering. However, only in the last two decades, the increase in computational power allowed the implementation of metaheuristic optimization techniques with promising results in research and practice. Pavement management requires powerful optimization tools for multi-objective problems such as minimizing costs and maximizing the pavement state from network to project level with constrained budgets. A substantial amount of research focuses on genetic algorithms (GA), but new developments include particle intelligence (PSO, ACO, and ABC). The study must go beyond small-sized networks to improve the management of existing road infrastructure (pavement, bridges) based on mechanistic and reliability criteria.

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