White-Tailed Eagle Algorithm for Global Optimization and Low-Cost and Low-CO 2 Emission Design of Retaining Structures

Behdad Arandian, Amin Iraji (), Hossein Alaei, Suraparb Keawsawasvong and Moncef L. Nehdi ()
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Behdad Arandian: Department of Electrical Engineering, Dolatabad Branch, Islamic Azad University, Isfahan 8441811111, Iran
Amin Iraji: Engineering Faculty of Khoy, Urmia University of Technology, Urmia 5716693188, Iran
Hossein Alaei: Department of Civil Engineering, Qaemshahr Branch, Islamic Azad University, Qaemshahr 1477893855, Iran
Suraparb Keawsawasvong: Department of Civil Engineering, Thammasat School of Engineering, Thammasat University, Bangkok 52190, Thailand
Moncef L. Nehdi: Department of Civil Engineering, McMaster University, Hamilton, ON L8S 4M6, Canada

Sustainability, 2022, vol. 14, issue 17, 1-28

Abstract: This study proposes a new metaheuristic optimization algorithm, namely the white-tailed eagle algorithm (WEA), for global optimization and optimum design of retaining structures. Metaheuristic optimization methods are now broadly implemented to address problems in a variety of scientific domains. These algorithms are typically inspired by the natural behavior of an agent, which can be humans, animals, plants, or any physical agent. However, a specific metaheuristic algorithm (MA) may not be able to find the optimal solution for every situation. As a result, researchers will aim to propose and discover new methods in order to identify the best solutions to a variety of problems. The white-tailed eagle algorithm (WEA) is a simple but effective nature-inspired algorithm inspired by the social life and hunting activity of white-tailed eagles. The WEA’s hunting is divided into two phases. In the first phase (exploration), white-tailed eagles seek prey inside the searching region. The eagle goes inside the designated space according to the position of the best eagle to find the optimum hunting position (exploitation). The proposed approach is tested using 13 unimodal and multimodal benchmark test functions, and the results are compared to those obtained by some well-established optimization methods. In addition, the new algorithm automates the optimum design of retaining structures under seismic load, considering two objectives: economic cost and CO 2 emissions. The results of the experiments and comparisons reveal that the WEA is a high-performance algorithm that can effectively explore the decision space and outperform almost all comparative algorithms in the majority of the problems.

Keywords: nature-inspired; white-tailed eagle; retaining structure; cost; CO 2 emissions (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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