中文版 | English
题名

Reliability of Indicator-Based Comparison Results of Evolutionary Multi-objective Algorithms

作者
通讯作者Ishibuchi, Hisao
DOI
发表日期
2024
会议名称
18th International Conference on Parallel Problem Solving from Nature, PPSN 2024
ISSN
0302-9743
EISSN
1611-3349
ISBN
9783031700842
会议录名称
卷号
15151 LNCS
页码
285-298
会议日期
September 14, 2024 - September 18, 2024
会议地点
Hagenberg, Austria
出版者
摘要
In evolutionary multi-objective optimization (EMO), performance indicators are often used to measure the quality of non-dominated solution sets obtained by EMO algorithms. However, the reliability of the performance indicators has not been well studied. In this paper, we compare the quality of non-dominated solution sets using four performance indicators: hypervolume (HV), inverted generational distance (IGD), inverted generational distance+ (IGD+), and additive epsilon (ϵ+). Our experimental results show that different performance indicators produce similar results when they are applied to commonly-used benchmark test problems such as DTLZ1 and DTLZ2. However, for real-world problems, we obtained significantly different comparison results from these indicators. Even when we use the same HV indicator, we obtain significantly different results depending on the reference point specifications. These observations suggest the importance of the choice of an indicator for performance comparison of EMO algorithms on real-world problems. When the HV indicator is used, the choice of a reference point is also important. Moreover, our observations suggest the necessity of using multiple indicators (including the HV indicator with multiple reference points) to obtain reliable performance comparison results.
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
学校署名
第一 ; 通讯
语种
英语
收录类别
资助项目
This work was supported by National Natural Science Foundation of China (Grant No. 62250710163, 62376115), Guangdong Provincial Key Laboratory (Grant No. 2020B121201001).
EI入藏号
20243917095159
EI主题词
Multiobjective optimization
EI分类号
:1106.2 ; :1201.7
来源库
EV Compendex
引用统计
成果类型会议论文
条目标识符http://sustech.caswiz.com/handle/2SGJ60CL/841063
专题工学院_计算机科学与工程系
南方科技大学
作者单位
Guangdong Provincial Key Laboratory of Brain-inspired Intelligent Computation, Department of Computer Science and Engineering, Southern University of Science and Technology, Shenzhen; 518055, China
第一作者单位计算机科学与工程系
通讯作者单位计算机科学与工程系
第一作者的第一单位计算机科学与工程系
推荐引用方式
GB/T 7714
Pang, Lie Meng,Ishibuchi, Hisao,Nan, Yang,et al. Reliability of Indicator-Based Comparison Results of Evolutionary Multi-objective Algorithms[C]:Springer Science and Business Media Deutschland GmbH,2024:285-298.
条目包含的文件
条目无相关文件。
个性服务
原文链接
推荐该条目
保存到收藏夹
查看访问统计
导出为Endnote文件
导出为Excel格式
导出为Csv格式
Altmetrics Score
谷歌学术
谷歌学术中相似的文章
[Pang, Lie Meng]的文章
[Ishibuchi, Hisao]的文章
[Nan, Yang]的文章
百度学术
百度学术中相似的文章
[Pang, Lie Meng]的文章
[Ishibuchi, Hisao]的文章
[Nan, Yang]的文章
必应学术
必应学术中相似的文章
[Pang, Lie Meng]的文章
[Ishibuchi, Hisao]的文章
[Nan, Yang]的文章
相关权益政策
暂无数据
收藏/分享
所有评论 (0)
[发表评论/异议/意见]
暂无评论

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。