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化工学报  2014 

一种求解化工动态优化问题的迭代自适应粒子群方法

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Keywords: 动态优化,迭代自适应粒子群,区域缩减,反应器

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Abstract:

因为其简单、易实现且具有良好的全局搜索能力,智能优化方法在动态优化中的应用越来越广泛,但传统的智能方法收敛速度相对较慢。本文提出了一种迭代自适应粒子群优化方法(iterativelyadaptiveparticleswarmoptimization,IAPSO)来求解一般的化工动态优化问题。首先通过控制变量参数化将原动态优化问题转化为非线性规划问题,再利用本文提出的迭代自适应粒子群优化方法进行求解。相比传统的粒子群优化方法,该种迭代自适应粒子群优化方法具有收敛速度更快的优点,主要原因是:1)该算法根据粒子种群分布特性自适应调整参数;2)该算法通过缩减搜索空间并迭代使用粒子群算法搜索最优解。本文将提出的迭代自适应粒子群方法应用到多个经典动态优化问题中,测试结果表明,该方法简单、有效,精度高,且收敛速度比传统粒子群算法有显著提升。

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