In this study, the seismic optimization design of assembled structure is discussed, and the genetic annealing algorithm is used for continuous optimization to establish assembled frame structure. In this paper, the genetic annealing algorithm is used for optimization. Firstly, the model of the assembled frame structure is established, including the three-dimensional model of the structure, material parameters, connection methods, constraints and so on. Then according to the choice of objective function and optimization variables, the corresponding constraints and parameter settings are set. Through these three processes of simulating the cooling process and the fitness function selection mechanism, the genetic annealing algorithm is adopted to carry out optimization to find the optimal solution. In the end, the optimized structure is analyzed and verified, and the structure optimized can effectively improve seismic performance and safety.

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Optimal Seismic Design of Assembled Frame Structure Based on Genetic Annealing Algorithm

  • Xiaowei Wang,
  • Dongping Hu,
  • Xinyu Fan

摘要

In this study, the seismic optimization design of assembled structure is discussed, and the genetic annealing algorithm is used for continuous optimization to establish assembled frame structure. In this paper, the genetic annealing algorithm is used for optimization. Firstly, the model of the assembled frame structure is established, including the three-dimensional model of the structure, material parameters, connection methods, constraints and so on. Then according to the choice of objective function and optimization variables, the corresponding constraints and parameter settings are set. Through these three processes of simulating the cooling process and the fitness function selection mechanism, the genetic annealing algorithm is adopted to carry out optimization to find the optimal solution. In the end, the optimized structure is analyzed and verified, and the structure optimized can effectively improve seismic performance and safety.