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A platform for research: civil engineering, architecture and urbanism
Design Optimization of Practical Tall Concrete Buildings Using Hybrid Optimality Criteria and Genetic Algorithms
The Optimality Criteria (OC) method has been a widely accepted structural optimization approach for large practical structures although there is no guarantee that the OC approach can always converge to a solution point. Genetic Algorithms (GAs) are gradient-free global searching algorithms, but require large number of reanalyses. In this paper, a hybrid optimization algorithm incorporating the OC and GA methods and utilizing both of their advantages is presented for the design of tall concrete building structures. A practical 42-story concrete building is used as the illustrative example and the results are discussed. The so-called hybrid OC-GA method is shown to be efficient and robust for structural optimization of tall concrete buildings.
Design Optimization of Practical Tall Concrete Buildings Using Hybrid Optimality Criteria and Genetic Algorithms
The Optimality Criteria (OC) method has been a widely accepted structural optimization approach for large practical structures although there is no guarantee that the OC approach can always converge to a solution point. Genetic Algorithms (GAs) are gradient-free global searching algorithms, but require large number of reanalyses. In this paper, a hybrid optimization algorithm incorporating the OC and GA methods and utilizing both of their advantages is presented for the design of tall concrete building structures. A practical 42-story concrete building is used as the illustrative example and the results are discussed. The so-called hybrid OC-GA method is shown to be efficient and robust for structural optimization of tall concrete buildings.
Design Optimization of Practical Tall Concrete Buildings Using Hybrid Optimality Criteria and Genetic Algorithms
Chan, Chun-Man (author) / Liu, Peng (author)
Eighth International Conference on Computing in Civil and Building Engineering (ICCCBE-VIII) ; 2000 ; Stanford, California, United States
2000-08-04
Conference paper
Electronic Resource
English
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