改进的精英教学优化算法及其在甲醇合成优化中的应用

发布时间：2018-05-09 13:18

本文选题：算法 + 甲醇合成　；参考：《化工学报》2017年08期

【摘要】：为了提高精英教学算法(ETLBO)的寻优能力,特别是精度差、寻优速度慢的问题,提出改进的精英教学算法。首先,通过自主学习过程,加强对优质解所在区域的局部勘探,提高算法的寻优效率。其次,引入"差异化帮扶"思想及自适应机制,对不同水平的学生施予适宜的、灵活的学习方式,有针对性的帮助,平衡了算法的勘探速度、精度。通过增加学生间的交流次数,提高了算法的全局勘探能力。标准函数优化结果表明,改进后的算法在寻优能力和勘探效率两方面都有明显提高。最后,建立甲醇合成的机理模型,将改进后的算法应用于甲醇合成过程的优化,取得了良好的效果。
[Abstract]:In order to improve the optimization ability of elite teaching algorithm, especially the problems of poor precision and slow optimization speed, an improved elite teaching algorithm is proposed. Firstly, through the autonomous learning process, the local exploration of the high quality solution area is strengthened, and the optimization efficiency of the algorithm is improved. Secondly, the idea of "differential help" and the adaptive mechanism are introduced to give appropriate and flexible learning methods to students at different levels and to help them, thus balancing the exploration speed and precision of the algorithm. By increasing the number of communication between students, the global exploration ability of the algorithm is improved. The results of standard function optimization show that the improved algorithm has significant improvement in both optimization ability and exploration efficiency. Finally, the mechanism model of methanol synthesis is established, and the improved algorithm is applied to the optimization of methanol synthesis process, and good results are obtained.
【作者单位】：华东理工大学化工过程先进控制与优化技术教育部重点实验室;
【基金】：国家自然科学基金项目(61573144)~~
【分类号】：TP18;TQ223.121

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