Accurate determination of near-surface responses of asphalt pavements

The construction of asphalt pavements in streets and highways is an activity that requires optimizing the consumption of significant economic and natural resources.Pavement design optimization meets contradictory objectives according to the availability of resources and users' needs.This dissertation explores the application of metaheuristics to optimize the design of asphalt pavements using an incremental design based on the prediction of damage and vehicle operating costs (VOC).The costs are proportional to energy and resource consumption and polluting emissions.The evolution of asphalt pavement design and metaheuristic optimization techniques on this topic were reviewed.Four computer programs were developed: (1) UNLEA, a program for the structural analysis of multilayer systems.(2) PSO-UNLEA, a program that uses particle swarm optimization metaheuristic (PSO) for the backcalculation of pavement moduli.(3) UNPAVE, an incremental pavement design program based on the equations of the North American MEPDG and includes the computation of vehicle operating costs based on IRI.(4) PSO-PAVE, a PSO program to search for thicknesses that optimize the design considering construction and vehicle operating costs.The case studies show that the backcalculation and structural design of pavements can be optimized by PSO considering restrictions in the thickness and the selection of materials.Future developments should reduce the computational cost and calibrate the pavement performance and VOC models.