基于 TILS 算法的汽轮机叶片排序方法

To reduce the residual unevenness after installation by optimizing the installation sequence of turbine blades，a threshold iterative local search algorithm (TILS) was proposed. Based on the iterative local search algorithm (ILS)， this algorithm adopted the combination of threshold limited disturbance and random disturbance to escape from local optimum，which reduced the number of iteration steps required to reach the local optimal solution on average. Experiments demonstrated that this method can find the approximately optimal combination of blade sequences in a relatively short time， which improved the search efficiency by more than 20% compared with the ILS algorithm. Compared with existing group sorting methods， genetic algorithms， and cloud adaptive genetic algorithm (CAGA) algorithms，the approximately optimal solution of synthetic mass product calculated by this algorithm was reduced to 0.33%—31%，and the computation time was significantly shorter.