Document Type

Article

Publication Date

2014

Journal or Book Title

Engineering with Computers

Volume

30

Issue

1

First Page

1

Last Page

13

DOI

10.1007/s00366-012-0281-y

Abstract

This paper focuses on the development of a new backcalculation method for concrete road structures based on a hybrid evolutionary global optimization algorithm, namely shuffled complex evolution (SCE). Evolutionary optimization algorithms are ideally suited for intrinsically multi-modal, non-convex, and discontinuous real-world problems such as pavement backcalculation because of their ability to explore very large and complex search spaces and locate the globally optimal solution using a parallel search mechanism as opposed to a point-by-point search mechanism employed by traditional optimization algorithms. SCE, a type of evolutionary optimization algorithms based on the tradeoff of exploration and exploitation, has proved to be an efficient method for many global optimization problems and in some cases it does not suffer the difficulties encountered by other evolutionary computation techniques. The SCE optimization approach is hybridized with a neural networks surrogate finite-element based forward pavement response model to enable rapid computation of global or near-global pavement layer moduli solutions. The proposed rigid pavement backcalculation model is evaluated using field non-destructive test data acquired from a full-scale airport pavement test facility.

Research Focus Area

Transportation Engineering

Comments

This is a manuscript of an article from Engineering with Computers 30 (2014): 1, doi: 10.1007/s00366-012-0281-y. The final publication is available at Springer via http://dx.doi.org/10.1007/s00366-012-0281-y.

Copyright Owner

Springer-Verlag London Limited

Language

en

File Format

application/pdf

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