关键词: 建筑节能优化, 粒子群变异算法, 算法改进, 计算机辅助建筑设计

Abstract: When particle swarm optimization algorithm is used in the building energy-saving optimization，it is easy to converge untimely in the local optima due to the multi-peak characteristic of the building energy model． The combination of the distributed mutation operator and particle swarm algorithm can provide a solution to this pro-blem． In this paper，4 existing particle swarm mutation algorithms were studied． Aiming at the problem of low effects of optimization，the specific operations of the mutations were improved，and the effectiveness of 4 improved algo-rithms was verified by test functions． Then，they were applied to a building energy-saving optimization case． Experi-mental results show that，as compared with the existing particle swarm mutation algorithms，the improved algorithm can decrease the average value of object function by 1. 3% at least and increase the convergence rate by over 3 times，which means that the optimization effect is obviously improved． Thus，it is concluded that the improved al-gorithms is effective and applicable in general building energy-saving optimization．

Key words: building energy-saving optimization, particle swarm mutation algorithm, algorithm improvement, computer-aided architecture design