Selection of Genetic Algorithm Parameters for Backcalculation of Pavement Moduli

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Abstract
In the context of pavement evaluation, backcalculation is the process of estimation of elastic properties of pavement layers using measured structural responses. A number of backcalculation programs are available for estimating effective pavement layer moduli from surface deflections. Different optimization techniques have been used in the development of these backcalculation models. Genetic algorithm (GA) has been used successfully in the recent past for backcalculation of pavement layer moduli. Selection of appropriate GA parameters is important for the efficient performance of the GA-based algorithm. However, there are no general guidelines available at present for the selection of GA parameters. This paper presents a study conducted for the selection of optimal GA parameters to be adopted for backcalculation of pavement layer moduli. The parameters have been selected on the basis of the level of accuracy desired and the corresponding computational effort (CE). The performance of the GA-based program with the selected parameters was evaluated using some hypothetical and field problems.

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