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遗传算法是一类随机优化方法，常被用于解决复杂的优化问题，基于群体的搜索、重组和变异是遗传算法区别于其他优化方法的主要特征。文章中将遗传算法应用于过饱和溶液Ｌｉ２Ｏ·３Ｂ２Ｏ３—Ｈ２Ｏ体系结晶过程动力学参数辨识，确定了结晶反应速率常数、热力学平衡浓度和表观反应级数。对于影响遗传算法的因素包括群体规模、重组率和变异率进行了研究，结果表明，当群体规模达到一定程度时，分别改变重组率和变异率并不总是能够改进问题的解。由遗传算法辨识得到的结晶动力学方程具有较高的精度，表明遗传算法可以作为一种有效的参数辨识方法。
Genetic algorithm is a kind of stochastic optimization method, which is often used to solve complex optimization problems. Group-based search, reorganization and mutation are the main features of genetic algorithms that are different from other optimization methods. In this paper, the genetic algorithm is applied to the kinetic parameter identification of the crystallization process of supersaturated Li2O · 3B2O3-H2O system, and the crystallization reaction rate constant, thermodynamic equilibrium concentration and apparent reaction order are determined. The factors affecting the genetic algorithm, including population size, recombination rate and mutation rate, are studied. The results show that when the population size reaches a certain level, changing the recombination rate and mutation rate separately can not always improve the solution of the problem. The crystal kinetic equation identified by genetic algorithm has high precision, indicating that genetic algorithm can be used as an effective parameter identification method.