非线性蒸汽动力系统参数优化新方法——改进遗传算法  

A Method for Optimization of Utility System ? Improved Genetic Algorithm

作　　者：王克峰[1] 修乃云[1] 匡国柱[1] 姚平经[1] 袁一[1] 

机构地区：[1]大连理工大学化工学院化工系统工程研究所

出　　处：《化学工程》1998年第4期42-45,55,共5页Chemical Engineering(China)

基　　金：国家自然科学基金

摘　　要：针对蒸汽动力系统参数优化的整数非线性规划问题（ＮＬＰ）提出一种改进的遗传算法。该算法对连续变量采用连续化遗传算子进行处理，使得算法与原问题的对应更加自然有效。针对常见的提前收敛或局部最小现象提出几种算子。实例表明本方法能对蒸汽动力系统参数准确、迅速地进行优化。An improved genetic algorithm(IGA) is presented for the optimization of utility system which can be described as the problem of nonlinear programming (NLP). In the algorithm,continuous genetic operators are used for continuous variables,at the same time,several operators are set up to deal with the usual phenomenon of premature convergence and local optimum.Examples show that IGA has the ability of finding the global optimum with higher speed and better precision than traditional genetic algorithm.

关 键 词：蒸汽 动力系统 改进遗传算法 最优化 化工厂 

分 类 号：TQ083.3[化学工程]