改进生物地理学算法对正丁烷异构反应模型的优化

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。

Kinetic model optimization of n-butane isomerization by improved biogeography optimization algorithm

To overcome the problem that biogeography-based optimization (BBO) algorithm easily falls into precocity in optimization process, a three-dimensional variation biogeography-based optimization (Tdv-BBO) was proposed. With introduction of 3D variation into BBO algorithm, the improved algorithm solved issue of lack of searching 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. The simulation results show that Tdv-BBO algorithm improves diversity of individual population, enhances searching capacity of algorithm, and accelerates optimization speed. The optimized kinetic model by Tdv-BBO has advantages of high precision and good generalization ability. Hence, Tdv-BBO provides an effective technique for modeling n-butane isomerization.