摘要
化工过程的多目标优化综合问题可归结为多目标混合整数非线性规划(MOMINLP)模型的求解,求解方法主要有数学规划法和多目标进化算法。以多目标遗传算法(MOGA)为代表的进化算法被认为是特别适合求解此类问题。遗传算法大多用于单目标问题的优化,近十几年来将遗传算法应用到多目标优化的研究得到了很大的发展。本文对多目标遗传算法的一些重要概念、发展历程进行了回顾。针对化工过程的模型特点,对MOGA在过程综合中的应用研究进行了讨论,并认为混合遗传算法应是求解此类问题的有效算法。
Muhiobjective process synthesis can be formulated as a muhiobjective mixed integer nonlinear programming （MOMINLP） problem. Mathematical program and mutiobjective genetic algorithm（MOGA） are often used to solve this problem. MOGA is regarded as a prospective method. GA is often used to optimize single objective problem. In the past decade the study of GA on muhiobjective optimization has been developed rapidly. In this paper, some important concepts of MOGA are discussed and the development of MOGA is reviewed. The research direction of MOGA used in chemical engineering synthesis is discussed and hybrid MOGA is regarded as a efficient strategy.
出处
《计算机与应用化学》
CAS
CSCD
北大核心
2006年第8期748-752,共5页
Computers and Applied Chemistry
关键词
多目标优化
MOGA
过程综合
混合算法
muhiobjective optimization, MOGA, process synthesis, hybrid algorithm
