多目标优化算法与其在化工中的应用-研究

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1、fractionationcolumnoperationparameter,theParetosetsweregiventochoose;(4)TosolvethedrawbacksofprematureconvergenceandlowcomputationalefficiencyofNSGA-II,ahybridalgorithmwasproposedwhichcouplesMOLCAandNSGA-II,namelyMOLCA-NSGA-II.Itperformedbetterinconvergence,di

2、stributionandoperatingefficiencyonthetestproblemsthanNSGA-II.DoubleobjectiveofrecoveryofolefinsandenergyconsumptioninMTOseparationprocessareoptimizedbyMOLCA-NSGA-IIontheAspenPlusandMATLABintegrationplatform,whichprovidingmeaningfulguidanceforthepracticaloperat

3、ion.Keywords:multi-objectiveoptimization,Line-upCompetition,MOLCA,NSGA-II,processsimulationIII万方数据目录中文摘要...............................................................................................................IAbstract....................................

4、.............................................................................II第1章绪论.......................................................................................................11.1研究的背景与意义.............................................................

5、...................11.2研究现状分析........................................................................................21.2.1多目标优化算法的研究进展......................................................21.2.2多目标优化算法的应用进展.....................................................

6、.41.2.3列队竞争算法的研究与应用进展.............................................51.3本文研究内容........................................................................................6第2章非支配遗传算法和列队竞争算法基础知识.......................................82.1多目标优化问题........................

7、............................................................82.1.1多目标优化问题的描述.............................................................82.1.2Pareto优化的相关定义...............................................................82.2列队竞争算法LCA............................

8、.................................................102.2.1算法框架...................................................................................102.2.2主要操作算子........................