In addition, CS presents a promising performance in reaching the optimum solutions that are better than GA, PSO, and GSA. Backcalculation of Pavement Layer Moduli: Asphalt Pavement. Obtained results indicate that the proposed backcalculation approach is able to determine stiffness-related layer properties in an accurate and rapid manner. In addition, to evaluate the searching capability of CS, optimization algorithms widely used in pavement backcalculation Genetic Algorithms (GA), Particle Swarm Optimization (PSO), and Gravitational Search Algorithm (GSA), are employed for comparison purposes. We benchmark our major pavement designs within an international group of practitioners using a range of software, and Rubicon is seen as the de-facto reference standard.
The performance of the proposed method is investigated by analyzing the synthetically calculated deflections by a finite element based software and deflection data obtained from the field. Executable file Download BACKGENETIC3D.EXE For further information or assistance on this program, please contact Ali Sangghaleh at (4) Reference An Efficient and Accurate Genetic Algorithm for Backcalculation of Flexible Pavement Layer Moduli, 2012, FHWA/OH-2012/18, Ernian Pan, Ohio DOT. Rubicon gives me a great sense of confidence when using it as design software. In the backward phase of the method, Cuckoo Search (CS), is utilized to search for the layer moduli values. The proposed algorithm, namely CS-ANN, uses an Artificial Neural Network (ANN) based forward response engine, which is developed from the solutions of nonlinear finite element analysis to calculate the deflections mathematically. This study introduces a backcalculation algorithm to estimate the material properties of the full-depth asphalt pavements. Springer Tracts in Nature-Inspired Computing