基于改进Alopex算法的烷基化生产过程的优化  

Optimizing the production process of alkylation based on modified alopex algorithm

作　　者：闫生辉[1] 张玉婷[1] 李道军[1] 卢青波[1] 

机构地区：[1]郑州职业技术学院,河南郑州450121

出　　处：《化学研究与应用》2012年第7期1106-1111,共6页Chemical Research and Application

基　　金：河南省科技攻关计划项目(2010C46008)资助;河南省高等学校青年骨干教师资助计划项目(2011GGJS_296)资助

摘　　要：为了提高Alopex算法的全局搜索能力,本文提出了一种改进的Alopex算法。该算法将混沌算法引入到Alopex的初始化过程中,提出了具有停滞行为的步长操作方法,在个体连续一定代数没有更新时,引入了高斯变异操作。最后利用改进的Alopex算法求解了烷基化生产过程的最优化问题,优化结果表明了本文算法的有效性。In order to enhance the global searching ability of Alopex algorithm,a modified Alopex algorithm is proposed.The new algorithm incorporated the chaotic algorithm to initialize the individuals and proposed a step operation method with stagnation behavior.The new algorithm also incorporated the Gauss mutation method when one individual was not updated at certain iteration.The improved Alopex algorithm was used to solve the optimization problem of alkylation＇s production process and the good results showed the effectiveness of this algorithm.

关 键 词：ALOPEX算法 烷基化 混沌算法 高斯变异 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]