智能算法在蒸汽管网保温层厚度优化设计中的应用

Application of intelligent algorithms in the optimal design of insulation thickness of steam networks

目的:研究不同智能算法在蒸汽管网保温层厚度优化设计中的应用。方法:根据管网保温层的建设成本与管网散热成本构建蒸汽管网保温层年折算成本模型,分别采用改进遗传算法、粒子群算法和模拟退火算法对管网保温层厚度进行优化设计,从算法的目标函数大小、解集的优劣等方面分析不同算法在保温层厚度优化设计中的适用性及特点。结果:虽然改进遗传算法的迭代次数最少,但由于其和粒子群算法收敛的解集不合理,因此模拟退火算法求得的保温层厚度值更符合工程实际。结论:在工业蒸汽管网保温层厚度优化设计中推荐使用模拟退火算法。

Aims:This paper aims to research the application of different intelligent algorithms in the optimization design of the thickness of the insulation layer of the steam network.Methods:According to the insulation layer construction and the heat dissipation cost of the pipe network,the annual conversion cost model of the steam network insulation layer was constructed;and the improved genetic algorithm,the particle swarm algorithm and the simulated annealing algorithm were used to optimize the thickness of the pipe network insulation layer.The applicability and characteristics of different algorithms in the optimization design were analyzed in terms of the size of the objective function of the algorithm and the pros and cons of the solution set.Results:The number of iterations of the improved genetic algorithm was the least;but the value of convergence with the particle swarm algorithm was unreasonable.The value of the insulation thickness obtained by the simulated annealing algorithm was more in line with the industrial application.Conclusions:The simulated annealing algorithm is recommended in the optimization design of the insulation thickness of the industrial steam network.