Table of Contents Author Guidelines Submit a Manuscript
Mathematical Problems in Engineering
Volume 2014, Article ID 474289, 10 pages
Research Article

Multigene Genetic Programming for Estimation of Elastic Modulus of Concrete

1Department of Civil Engineering, Islamic Azad University, Kashmar Branch, Kashmar, Iran
2School of Computer Science and Technology, Jiangsu Normal University, Xuzhou, Jiangsu 221116, China
3Department of Civil Engineering, Islamic Azad University, Bandar Abbas Branch, Bandar Abbas, Iran
4Department of Civil and Environmental Engineering, Michigan State University, East Lansing, MI 48824, USA
5Department of Civil Engineering, The University of Akron, Akron, OH 44325, USA

Received 25 January 2014; Accepted 4 April 2014; Published 29 April 2014

Academic Editor: Siamak Talatahari

Copyright © 2014 Alireza Mohammadi Bayazidi et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


This paper presents a new multigene genetic programming (MGGP) approach for estimation of elastic modulus of concrete. The MGGP technique models the elastic modulus behavior by integrating the capabilities of standard genetic programming and classical regression. The main aim is to derive precise relationships between the tangent elastic moduli of normal and high strength concrete and the corresponding compressive strength values. Another important contribution of this study is to develop a generalized prediction model for the elastic moduli of both normal and high strength concrete. Numerous concrete compressive strength test results are obtained from the literature to develop the models. A comprehensive comparative study is conducted to verify the performance of the models. The proposed models perform superior to the existing traditional models, as well as those derived using other powerful soft computing tools.