Improved bat algorithm for structural reliability assessment: application and challenges
Multidiscipline Modeling in Materials and Structures
ISSN: 1573-6105
Article publication date: 8 August 2016
Abstract
Purpose
The first order reliability method requires optimization algorithms to find the minimum distance from the origin to the limit state surface in the normal space. The purpose of this paper is to develop an improved version of the new metaheuristic algorithm inspired from echolocation behaviour of bats, namely, the bat algorithm (BA) dedicated to perform structural reliability analysis.
Design/methodology/approach
Modifications have been embedded to the standard BA to enhance its efficiency, robustness and reliability. In addition, a new adaptive penalty equation dedicated to solve the problem of the determination of the reliability index and a proposition on the limit state formulation are presented.
Findings
The comparisons between the improved bat algorithm (iBA) presented in this paper and other standard algorithms on benchmark functions show that the iBA is highly efficient, and the application to structural reliability problems such as the reliability analysis of overhead crane girder proves that results obtained with iBA are highly reliable.
Originality/value
A new iBA and an adaptive penalty equation for handling equality constraint are developed to determine the reliability index. In addition, the low computing time and the ease implementation of this method present great advantages from the engineering viewpoint.
Keywords
Acknowledgements
The authors would like to express their acknowledgements to the staff of Metal Steel Annaba for providing us with the necessary data of the overhead travelling crane. In addition, they would also acknowledge the useful comments and suggestions of the unknown reviewers, which improved the presentation.
Citation
Chakri, A., Khelif, R. and Benouaret, M. (2016), "Improved bat algorithm for structural reliability assessment: application and challenges", Multidiscipline Modeling in Materials and Structures, Vol. 12 No. 2, pp. 218-253. https://doi.org/10.1108/MMMS-07-2015-0035
Publisher
:Emerald Group Publishing Limited
Copyright © 2016, Emerald Group Publishing Limited