Building Construction Design Based on Particle Swarm Optimization Algorithm

Abstract

In order to take a scientific risk control strategy to reduce the safety risk of construction projects, a construction safety risk decision-making method based on particle swarm optimization algorithm was proposed. Through the analysis of prefabricated building construction safety risk factors, the combination of the Markov Chain and Bayesian networks method was used to estimate the probability of risk factors. The relationship between the various risk factors was described by conditional probability, and a safety risk loss-control investment double objective optimization model was built. The corresponding algorithm was designed and the R language programming was used to solve the problem. The experimental results showed that by taking a high degree of control over the risk factors of the investment strategy, when the constraint cost was RMB 200,000, the global optimal risk loss and the global optimal control cost were RMB 1,400,500 and 19,600, respectively. When the constraint cost was 280,000 yuan, the global optimal risk loss and global optimal control cost were 1.046 million yuan and 278.5 million yuan, respectively. When the constraint cost was 320,000 yuan, the global optimal risk loss and global optimal control cost were 910,100 yuan and 317,300, yuan respectively. It was concluded that, considering the risk correlation optimization model, a reasonable allocation strategy was adopted, combined with the actual situation, which performed a promoting function in improving the assembly building construction safety risk decision-making.