摘要
针对生物地理学优化(biogeography-based optimization,BBO)算法在寻优过程中容易陷入早熟的现象,提出了一种基于三维变异的生物地理学优化(three-dimensional variation biogeography-based optimization,Tdv-BBO)算法。该算法是在BBO算法的基础上,引入了三维变量的变异,解决了BBO算法后期搜索动力不足的问题,加快了BBO算法的寻优速度。同时,提出将改进的Tdv-BBO算法应用到正丁烷异构反应动力学模型的优化中,对反应动力学模型的参数进行了优化和整定。仿真实验表明:改进的Tdv-BBO算法提高了个体种群的多样性,增强了算法的搜索能力,加快了寻优速度。用该方法优化得到的反应动力学模型,模型精度较高,泛化能力强;可为正丁烷异构反应的建模提供一种有效的方法。
To overcome the problem that biogeography-based optimization(BBO)algorithm easily falls intoprecocity in optimization process,a three-dimensional variation biogeography-based optimization(Tdv-BBO)wasproposed.With introduction of3D variation into BBO algorithm,the improved algorithm solved issue of lack ofsearching power in late stage of BBO algorithm and accelerated optimization speed of BBO algorithm.Further,Tdv-BBO was applied for optimizing kinetic model and settling model parameters of n-butane isomerization.Thesimulation results show that Tdv-BBO algorithm improves diversity of individual population,enhances searchingcapacity of algorithm,and accelerates optimization speed.The optimized kinetic model by Tdv-BBO has advantagesof high precision and good generalization ability.Hence,Tdv-BBO provides an effective technique for modeling nbutane isomerization.
作者
罗锐涵
陈娟
王齐
LUO Ruihan;CHEN Juan;WANG Qi(College of Information Science & Technology, Beijing University of Chemical Technology, Beijing 100029, China;Beijing Century Robust Technology Co.Ltd., Beijing 100020, China)
出处
《化工学报》
EI
CAS
CSCD
北大核心
2018年第3期1158-1166,共9页
CIESC Journal
基金
国家自然科学基金项目(21376014
61771034)~~
