微粒群算法在干燥器多变量优化设计中的应用

建立了以具有废气循环的回转干燥系统年总费用为目标函数的优化设计数学模型,在此基础上探讨了惯性权因子对微粒群算法性能的影响,并应用微粒群算法求解干燥器优化设计数学模型,对干燥器出口废气温度与循环比进行优化设计。结果表明,带动态非线性惯性因子的微粒群算法对求解多变量的干燥优化设计问题具有方法简单、所需微粒群规模小、收敛速度快等特点;采用部分废气循环并进行优化设计对干燥系统的节能具有十分重要的意义,对湿空气出口温度和废气循环比进行优化设计,其年总费用比无废气循环的常规设计节省18．2%,比循环比为0．2时的常规设计节省12．6%。

Application of particle swarm optimization algorithm in multivariable optimum design of dryer

The optimum design model of rotary dryer with exhaust gas recycle is established,which aimed at the annual total cost.The model is solved by particle swarm optimization(PSO)algorithm to re- alize the optimum design of humid air outlet temperature and exhaust gas recycle ratio.The effect of iner- tia weight factor on performance of PSO is discussed.The results show that the particle swarm optimiza- tion algorithm with nonlinear inertia weight factor is suitable to solve multivariahle optimum design prob- lem.PSO has many marked traits such as briefness,small scale and rapid convergence.The exhaust gas recycle(EGR)and optimum design are of great importance to energy saving of dry system.The annual to- tal cost of optimum design decreased by 18.20% than that of conventional design without EGR,12.6% than that of conventional design when exhaust gas recycle ratio is 0.2