Optimal Design of Planar Steel Frames Using the Hybrid Teaching–Learning and Charged System Search Algorithm

In this study, a novel effective algorithm called HTC which results from a hybridization process between the teaching–learning-based optimization (TLBO) and charged system search (CSS) algorithms is proposed and utilized to optimize planar steel frames. Among the features of the proposed algorithm,...

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Bibliographic Details
Published in:Iranian journal of science and technology. Transactions of civil engineering Vol. 47; no. 6; pp. 3357 - 3373
Main Authors: Dastan, Mohammadhossein, Goodarzimehr, Vahid, Shojaee, Saeed, Hamzehei-Javaran, Saleh, Talatahari, Siamak
Format: Journal Article
Language:English
Published: Cham Springer International Publishing 01.12.2023
Springer Nature B.V
Subjects:
Algorithms
Biogeography
Black holes
Civil Engineering
Coronaviruses
Design
Design factors
Design optimization
Engineering
Genetic algorithms
Heuristic methods
Hybridization
Learning
Limit state design
Methods
Minimum weight
Mutation
Optimization
Optimization algorithms
Performance evaluation
Physics
Research Paper
Resistance factors
Search algorithms
Steel
Steel frames
Theory of relativity
Viruses
Hybrid teaching–learning and charged system search algorithm
Metaheuristics
Optimization of steel frames
Optimal design
ISSN:2228-6160, 2364-1843
Online Access:Get full text
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Summary:In this study, a novel effective algorithm called HTC which results from a hybridization process between the teaching–learning-based optimization (TLBO) and charged system search (CSS) algorithms is proposed and utilized to optimize planar steel frames. Among the features of the proposed algorithm, simplicity and low number of setting parameters can be mentioned. The main goals of this hybridization process are to establish a balance between exploration and exploitation, increase the rate of convergence, and avoid getting trapped in the local optimal point. Moreover, the purpose of optimizing steel frames is to calculate their minimum weight by choosing suitable sections as well as considering the stress and displacement constraints in accordance with the requirements of the AISC design regulations using the load and resistance factor design (LRFD) method. To evaluate the performance of the HTC algorithm, standard benchmark steel frames are examined, and the results of the proposed algorithm are compared with other metaheuristic optimization methods. According to the outcomes of the comparison, the proposed algorithm has better performance than the other methods.
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ISSN:2228-6160
2364-1843
DOI:10.1007/s40996-023-01124-8