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内蒙古自治区呼和浩特市赛罕区大学西街235号 邮编: 010021
作者机构:Univ Santiago de Compostela Food Res Inst Dept Analyt Chem Nutr & Food Sci Santiago De Compostela Spain
出 版 物:《CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS》 (化学计量学与智能实验系统)
年 卷 期:2012年第114卷
页 面:72-86页
核心收录:
学科分类:07[理学] 0804[工学-仪器科学与技术] 0714[理学-统计学(可授理学、经济学学位)] 0703[理学-化学] 0701[理学-数学] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术(可授工学、理学学位)]
基 金:Spanish Ministry for Science and Innovation FEDER funds [CTQ 2009-08377]
主 题:Cluster maps Parallel coordinates plot Pareto front visualization Multi-objective optimization
摘 要:Two new graphical tools for the interpretation of Pareto fronts and the selection of non-dominated solutions produced in multi-objective optimization processes (MOOPs), are presented. The first is a version of the parallel coordinates plots (PCP), modified by combining the PCP with the dendrogram representing the cluster analysis of non-dominated solutions in the decision variable space or in the objective space. A correspondence plot that simplifies interpretation of the above plots has also been developed. The second graphical tool is a cluster map (PFCM), produced by combining the information provided by the dendrograms calculated in the decision and the objective spaces, to provide a two-dimensional plot in which the non-dominated solutions are organized according to both dendrograms: the plot is colored on the basis of any of the objectives or a combination of these objectives when convenient. Two derived graphic tools consisting of a combination of the decision variables and the objectives and the dendrograms produced in the decision and the objective spaces have also been developed. All of these graphical tools are demonstrated with several mathematical functions available in the MOOP-related literature and with a real-world optimization process consisting of the computer-assisted method development of high-performance liquid chromatography. (C) 2012 Elsevier B.V. All rights reserved.