TY - JOUR
T1 - Optimization of Large-Scale Frame Structures Using Fuzzy Adaptive Quantum Inspired Charged System Search
AU - Talatahari, Siamak
AU - Azizi, Mahdi
AU - Toloo, Mehdi
AU - Baghalzadeh Shishehgarkhaneh, Milad
N1 - Funding Information:
This research was supported by the University of Tabriz (Number: 1615) and the Czech Science Foundation (GAČR 19-13946S).
Funding Information:
This research was supported by the University of Tabriz (Number: 1615) and the Czech Science Foundation (GAČR 19-13946S). We would like to express our sincere gratitude and appreciation to Prof. Saeid Kazemzadeh Azad for providing the required data of the structural design examples.
Publisher Copyright:
© 2022, Korean Society of Steel Construction.
PY - 2022/6
Y1 - 2022/6
N2 - In this paper, a metaheuristic-based design approach is developed in which the structural design optimization of large-scale steel frame structures is concerned. Although academics have introduced form-dominant methods, yet using artificial intelligence in structural design is one of the most critical challenges in recent years. However, the Charged System Search (CSS) is utilized as the primary optimization approach, which is improved by using the main principles of quantum mechanics and fuzzy logic systems. In the proposed Fuzzy Adaptive Quantum Inspired CSS algorithm, the position updating procedure of the standard algorithm is developed by implementing the center of potential energy presented in quantum mechanics into the general formulation of CSS to enhance the convergence capability of the algorithm. Simultaneously, a fuzzy logic-based parameter tuning process is also conducted to enhance the exploitation and exploration rates of the standard optimization algorithm. Two 10 and 60 story steel frame structures with 1026 and 8272 structural members, respectively, are utilized as design examples to determine the performance of the developed algorithm in dealing with complex optimization problems. The overall capability of the presented approach is compared with the Charged System Search and other metaheuristic optimization algorithms. The proposed enhanced algorithm can prepare better results than the other metaheuristics by considering the achieved results.
AB - In this paper, a metaheuristic-based design approach is developed in which the structural design optimization of large-scale steel frame structures is concerned. Although academics have introduced form-dominant methods, yet using artificial intelligence in structural design is one of the most critical challenges in recent years. However, the Charged System Search (CSS) is utilized as the primary optimization approach, which is improved by using the main principles of quantum mechanics and fuzzy logic systems. In the proposed Fuzzy Adaptive Quantum Inspired CSS algorithm, the position updating procedure of the standard algorithm is developed by implementing the center of potential energy presented in quantum mechanics into the general formulation of CSS to enhance the convergence capability of the algorithm. Simultaneously, a fuzzy logic-based parameter tuning process is also conducted to enhance the exploitation and exploration rates of the standard optimization algorithm. Two 10 and 60 story steel frame structures with 1026 and 8272 structural members, respectively, are utilized as design examples to determine the performance of the developed algorithm in dealing with complex optimization problems. The overall capability of the presented approach is compared with the Charged System Search and other metaheuristic optimization algorithms. The proposed enhanced algorithm can prepare better results than the other metaheuristics by considering the achieved results.
KW - Design optimization
KW - Fuzzy adaptive quantum inspired charged system search
KW - Fuzzy logic
KW - Large-scale frame structure
KW - Metaheuristic
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U2 - 10.1007/s13296-022-00598-y
DO - 10.1007/s13296-022-00598-y
M3 - Article
AN - SCOPUS:85127655024
SN - 1598-2351
VL - 22
SP - 686
EP - 707
JO - International Journal of Steel Structures
JF - International Journal of Steel Structures
IS - 3
ER -