Optimal outrigger placement in tall steel frames using improved EEFO algorithm

The electric eel foraging optimisation EEFO algorithm and an improved variant (I-EEFO) were evaluated for optimising outrigger brace placement in full-scale steel frame structures. The I-EEFO algorithm integrates a Levy flight to replace traditional Brownian randomisation, improving exploration efficiency. Two design examples (10-storey and 20-storey steel frames) demonstrate the algorithms’ ability to enhance structural stability in high-rise buildings. Compared with established metaheuristic methods such as the grey wolf optimiser and the whale optimisation algorithm, the I-EEFO algorithm exhibited superior convergence speed, accuracy and robustness through rigorous evaluations. These findings establish the I-EEFO algorithm as a powerful tool for structural optimisation, offering significant potential for designing efficient and resilient tall buildings.

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Publication Details

Journal
Proceedings of the Institution of Civil Engineers - Structures and Buildings
Published
2026-02-24
DOI
https://doi.org/10.1680/jstbu.25.00137
Citations
1
Primary Topic
Seismic and Structural Analysis of Tall Buildings
Type
article
Field-Weighted Citation Impact
19.37
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article

Optimal outrigger placement in tall steel frames using improved EEFO algorithm

Hadi Azizian, Reza Sojoudizadeh, Loghman Rahimi, Vafa Jabbari
1 citations
Proceedings of the Institution of Civil Engineers - Structures and Buildings
Seismic and Structural Analysis of Tall Buildings
19.37
article

Optimal outrigger placement in tall steel frames using improved EEFO algorithm

Hadi Azizian, Reza Sojoudizadeh, Loghman Rahimi, Vafa Jabbari
article en
1 citations

Abstract

The electric eel foraging optimisation EEFO algorithm and an improved variant (I-EEFO) were evaluated for optimising outrigger brace placement in full-scale steel frame structures. The I-EEFO algorithm integrates a Levy flight to replace traditional Brownian randomisation, improving exploration efficiency. Two design examples (10-storey and 20-storey steel frames) demonstrate the algorithms’ ability to enhance structural stability in high-rise buildings. Compared with established metaheuristic methods such as the grey wolf optimiser and the whale optimisation algorithm, the I-EEFO algorithm exhibited superior convergence speed, accuracy and robustness through rigorous evaluations. These findings establish the I-EEFO algorithm as a powerful tool for structural optimisation, offering significant potential for designing efficient and resilient tall buildings.

Proceedings of the Institution of Civil Engineers - Structures and BuildingsVol. 179(2)
Islamic Azad University of Mahabad (IR)
Openalex Percentile: Top 1%
Seismic and Structural Analysis of Tall Buildings
19.37
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