Metaheuristic optimization of reinforced concrete footings

Nigdeli, Sinan Melih, Bekdaş, Gebrail and Yang, Xin-She ORCID: (2018) Metaheuristic optimization of reinforced concrete footings. KSCE Journal of Civil Engineering, 22 (11) . pp. 4555-4563. ISSN 1226-7988 [Article] (doi:10.1007/s12205-018-2010-6)

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The primary goal of an engineer is to find the best possible economical design and this goal can be achieved by considering multiple trials. A methodology with fast computing ability must be proposed for the optimum design. Optimum design of Reinforced Concrete (RC) structural members is the one of the complex engineering problems since two different materials which have extremely different prices and behaviors in tension are involved. Structural state limits are considered in the optimum design and differently from the superstructure members, RC footings contain geotechnical limit states. This study proposes a metaheuristic based methodology for the cost optimization of RC footings by employing several classical and newly developed algorithms which are powerful to deal with non-linear optimization problems. The methodology covers the optimization of dimensions of the footing, the orientation of the supported columns and applicable reinforcement design. The employed relatively new metaheuristic algorithms are Harmony Search (HS), Teaching-Learning Based Optimization algorithm (TLBO) and Flower Pollination Algorithm (FPA) are competitive for the optimum design of RC footings.

Item Type: Article
Research Areas: A. > School of Science and Technology > Design Engineering and Mathematics
Item ID: 24346
Notes on copyright: This is a post-peer-review, pre-copyedit version of an article published in KSCE Journal of Civil Engineering. The final authenticated version is available online at:
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Depositing User: Xin-She Yang
Date Deposited: 08 Jun 2018 08:47
Last Modified: 05 Mar 2022 00:53

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