过程系统中变约束粒子群算法的研究

Ding Qiang, Chen Hong, Chunlin Wang, Aipeng Jiang, Weiwei Lin
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引用次数: 1

摘要

针对具有可变约束和非刚性约束的化工问题,提出了一种基于粒子群优化算法(PSO)的求解方法。通过数学分析和变换,将变量约束作为优化项。然后将物品乘以惩罚并与主要目标函数相结合。将主要问题转化为多目标函数,利用多目标粒子群算法求解。利用多目标粒子群算法求解问题,并对涉及变量约束的解进行分析,得到合理的解和最优方案。将该方法应用于一个化工设计问题和一个参数估计问题的优化。结果表明,该方法是有效的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research of PSO algorithm with variable constraints in process system
To solve chemical problems with variable and nonrigid constraints, a method based on particle swarm optimization (PSO) algorithm was presented. By mathematical analysis and transform, the variable constraints were regard as an item to be optimized. Then the item multiplied by penalty and combined with the primary objective function. So the primary problem was transferred to the multi-objective function, and can be solved by multi-objective PSO algorithm. With problems solved by multi-objective PSO and analysis of the solutions related with variable constraints, reasonable solution and optimal scheme can be obtained. The proposed method was used to optimize a chemical design problem and a parameter estimation problem. The results demonstrate that the proposed method is effective.
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