Incorporation of implicit decision-maker preferences in multi-objective evolutionary optimization using a multi-criteria classification method

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• 作者：Laura Cruz-Reyes^a ; ^{lauracruzreyes@itcm.edu.mx}Author Vitae ; Eduardo Fernandez^b ; ^{eddyf@uas.edu.mx}Author Vitae ; Patricia Sanchez^c ; ^{jpatricia.sanchez@gmail.com}Author Vitae ; Carlos A. Coello Coello^d ; ^{ccoello@cs.cinvestav.mx}Author Vitae ; Claudia Gomez^a ; ^{claudia.gomez@itcm.edu.mx}Author Vitae
• 关键词：Evolutionary algorithms ; Multi-objective optimization ; Implicit preferences ; Multi-criteria sorting
• 刊名：Applied Soft Computing
• 出版年：2017
• 出版时间：January 2017
• 年：2017
• 卷：50
• 期：Complete
• 页码：48-57
• 全文大小：706 K
• 卷排序：50

文摘

An original idea for incorporating implicit decision-maker preferences in multi-objective evolutionary optimization is presented. The preferences are captured in a training set formed by solutions assigned to preference-ordered categories. New solutions are classified by a multi-criteria sorting method using the training set. This approach creates a selection pressure towards the region of interest of the decision-maker instead of the whole Pareto front. Test examples confirm that our method achieves a good characterization of the region of interest for the public project portfolio problem.