基于改进蚁狮算法的间歇反应釜优化方法研究

Research on Optimization Method of Batch Reactor based on Improved Ant Lion Algorithm

针对蚁狮算法易陷入局部极值点和收敛速度慢的问题,提出一种基于自适应边界调节策略和分段搜索策略的改进型蚁狮算法。通过引入自适应调节因子对蚂蚁围绕蚁狮游走时的范围进行自适应改变,提高了算法的全局寻优能力和寻优精度。融合粒子群算法的记忆保存思想和柯西变异算子对蚂蚁位置进行分段搜索,丰富了蚂蚁种群的多样性,解决了算法易陷入局部最优的问题。将改进的算法应用于乙酸乙酯生产过程的间歇式反应釜,并与蚁狮算法进行比较,实验表明改进后算法收敛速度更快,对间歇式反应釜生产过程中的反应温度、产物浓度和反应时间等参数的优化效果明显。

This paper proposes an improved ant lion algorithm based on adaptive boundaries and segmentation search strategy to address the problems that ant-lion algorithm tends to fall into local extremum and slow convergence speed.The adaptive adjustment factor is introduced to adaptively change the range of ants around the ant lion,which improves global search ability and search accuracy of the algorithm.The idea of memory preservation of particle swarm optimization and Cauchy mutation operator are combined to search the ant's position in segments,which enriches the diversity of ant population and solves the problem that the algorithm is easy to fall into local optimum.The improved algorithm is applied to the batch reactor of ethyl acetate production process.Compared with the traditional ant lion algorithm,experimental results show that the improved algorithm converges faster,and it has a better optimization effect on parameters,such as reaction temperature,product concentration and reaction time in the batch reaction production process.