Evaluating Multiobjective Evolutionary Algorithms Using MCDM Methods. (19th March 2018)

• Record Type: Journal Article
• Authors: Yu, Xiaobing; Lu, YiQun; Yu, Xianrui
• Other Names: Bigaud David Academic Editor.
• Is Part Of: Mathematical problems in engineering. Volume 2018(2018)
• Publication Date: 2018-03-19
• Subjects: Engineering mathematics -- Periodicals; 510.2462
• DOI: 10.1155/2018/9751783
• Languages: English
• ISSNs: 1024-123X

Abstract

Abstract : The evaluation of multiobjective evolutionary algorithms (MOEAs) involves many metrics, it can be considered as a multiple-criteria decision making (MCDM) problem. A framework is proposed to estimate MOEAs, in which six MOEAs, five performance metrics, and two MCDM methods are used. An experimental study is designed and thirteen benchmark functions are selected to validate the proposed framework. The experimental results have indicated that the framework is effective in evaluating MOEAs.