Backcalculation analysis of pavement-layer moduli using genetic algorithms

Abstract

Most existing iterative backcalculation programs for pavement layer moduli arrive at their solutions by minimizing an objective function related to the differences between computed and measured surface deflections. Unfortunately, the solution surface of the backcalculation problem of pavement-layer moduli is known to contain many local minima. A potentially good backcalculation procedure would be one that has a strong global search ability to overcome the problem of local minima. The genetic algorithm (GA) is a technique that satisfies this requirement. The development of a backcalculation program known as NUS-GABACK using the genetic-algorithm approach is presented, along with the formulation and operations of the program. A detailed performance evaluation of the GA-based method is made against four other programs by solving five backcalculation problems with different structural composition. It was found that NUS-GABACK performed comparably well against the other programs and demonstrated consistency in the accuracies of backcalculated moduli.