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Hybrid Stochastic Global Optimization Scheme for Rapid Pavement Backcalculation

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Intelligent and Soft Computing in Infrastructure Systems Engineering

Part of the book series: Studies in Computational Intelligence ((SCI,volume 259))

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Abstract

Over the years, several techniques have been proposed for back-calculation of pavement layer moduli which involves searching for the optimal combination of pavement layer stiffness solutions in an unsmooth, multimodal, complex search space. In recent years, researchers are actively deriving inspiration from nature, biology, physical systems, and social behavior of natural systems for developing computational techniques to solve complex optimization problems. Some well-known nature-inspired meta-heuristics, which are basically high-level strategies that guide the search process to efficiently explore the search space in order to find (near-) optimal solutions, include, but are not limited to: Genetic Algorithms (GA), Particle Swarm Optimization (PSO), Simulated Annealing (SA), Shuffled Complex Evolution (SCE), etc. Potential applications of such nature-inspired hybrid optimization approaches to pavement backcalculation are conceptually illustrated in this chapter which take advantage of the combined efficiency and accuracy achieved by integrating advanced pavement numerical modeling schemes, computational intelligence based surrogate mapping techniques, and stochastic nature-inspired meta-heuristics with global optimization strategies using a system-of-systems approach.

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Authors and Affiliations

  1. Iowa State University, Ames, IA, 50011, USA

    Kasthurirangan Gopalakrishnan

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  1. Kasthurirangan Gopalakrishnan
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Editors and Affiliations

  1. Dept. of Civil, Constr. & Env. Engg., Iowa State University, 354 Town Engineering Bldg., 50011-3232, Ames, IA, USA

    Kasthurirangan Gopalakrishnan

  2. Dept. of Civil, Constr. & Env. Engg., Iowa State University, 482B Town Engineering Bldg., 50011-3232, Ames, IA, USA

    Halil Ceylan

  3. Dept. of Civil and Environmental Engineering, University of Delaware, 343B DuPont Hall, DE 19716, Newark, USA

    Nii O. Attoh-Okine

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Gopalakrishnan, K. (2009). Hybrid Stochastic Global Optimization Scheme for Rapid Pavement Backcalculation. In: Gopalakrishnan, K., Ceylan, H., Attoh-Okine, N.O. (eds) Intelligent and Soft Computing in Infrastructure Systems Engineering. Studies in Computational Intelligence, vol 259. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04586-8_9

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  • DOI: https://doi.org/10.1007/978-3-642-04586-8_9

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-04585-1

  • Online ISBN: 978-3-642-04586-8

  • eBook Packages: EngineeringEngineering (R0)

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