A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Development of a Mutation Operator in a Real-Coded Genetic Algorithm for Bridge Model Optimization
https://orcid.org/https://orcid.org/0000-0002-9103-8578
https://orcid.org/https://orcid.org/0000-0002-2866-7590
A mutation operator in a real-coded genetic algorithm is developed and applied for efficient bridge-model optimization. A mutation operator that changes uniformly or dynamically with a crossover operator is proposed to address optimization problems. The performance of the combined genetic operators was verified using a variety of available test problems based on the convergence and search speed of the global optimal solution. It is shown that the genetic algorithm proposed in this study yields relatively better results than the available algorithms and is more effective in constrained optimization problems. The performance of the proposed genetic algorithm is also verified through a sample study using a field load test for the model optimization of an existing bridge.
Development of a Mutation Operator in a Real-Coded Genetic Algorithm for Bridge Model Optimization
https://orcid.org/https://orcid.org/0000-0002-9103-8578
https://orcid.org/https://orcid.org/0000-0002-2866-7590
A mutation operator in a real-coded genetic algorithm is developed and applied for efficient bridge-model optimization. A mutation operator that changes uniformly or dynamically with a crossover operator is proposed to address optimization problems. The performance of the combined genetic operators was verified using a variety of available test problems based on the convergence and search speed of the global optimal solution. It is shown that the genetic algorithm proposed in this study yields relatively better results than the available algorithms and is more effective in constrained optimization problems. The performance of the proposed genetic algorithm is also verified through a sample study using a field load test for the model optimization of an existing bridge.
Development of a Mutation Operator in a Real-Coded Genetic Algorithm for Bridge Model Optimization
https://orcid.org/https://orcid.org/0000-0002-9103-8578
https://orcid.org/https://orcid.org/0000-0002-2866-7590
A mutation operator in a real-coded genetic algorithm is developed and applied for efficient bridge-model optimization. A mutation operator that changes uniformly or dynamically with a crossover operator is proposed to address optimization problems. The performance of the combined genetic operators was verified using a variety of available test problems based on the convergence and search speed of the global optimal solution. It is shown that the genetic algorithm proposed in this study yields relatively better results than the available algorithms and is more effective in constrained optimization problems. The performance of the proposed genetic algorithm is also verified through a sample study using a field load test for the model optimization of an existing bridge.
Development of a Mutation Operator in a Real-Coded Genetic Algorithm for Bridge Model Optimization
KSCE J Civ Eng
Kim, Jaecheon (author) / Han, Manseok (author) / Shin, Soobong (author)
KSCE Journal of Civil Engineering ; 28 ; 1822-1835
2024-05-01
14 pages
Article (Journal)
Electronic Resource
English
Development of a Mutation Operator in a Real-Coded Genetic Algorithm for Bridge Model Optimization
| Springer Verlag | 2024
| British Library Online Contents | 2012
| British Library Online Contents | 2006
Diagnosing Crack of RC Structure Using Real-Coded Genetic Algorithm
| British Library Conference Proceedings | 2006
| British Library Online Contents | 2007