A hybrid inverse approach for estimating structural pavement parameters using the Differential Quadrature Method and a metaheuristic optimization algorithm

Abstract

This study proposes an efficient hybrid inverse computational method for the low-cost and accurate prediction of pavement layer moduli using a non-destructive testing technique, which holds significant practical importance. The hybrid approach integrates the Differential Quadrature Method (DQM), a highly accurate and computationally efficient direct problem-solving technique, with the Interactive Autodidactic School (IAS) metaheuristic optimization algorithm. The objective function of the proposed hybrid inverse method, referred to as the “DQM–IAS” technique, is formulated based on the relative differences between analytical and experimental pavement surface deflections. To evaluate the performance of the proposed method, two different three-layer pavement systems were simulated and analyzed. The results demonstrate that the DQM–IAS technique exhibits rapid convergence, high precision, and low computational cost. Therefore, the application of this technique is strongly recommended for road engineers to estimate the elastic moduli of pavement layers and assess the performance of complete pavement systems.

Graphical abstract

Keywords

pavement / backcalculation / axisymmetric multilayered half-space moduli / DQM / IAS

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