An Evolutionary Many-Objective Optimization Algorithm Using Reference-Point-Based Nondominated Sorting Approach, Part I: Solving Problems With Box Constraints

分类 多目标优化 进化算法 数学优化 最优化问题 计算机科学 集合(抽象数据类型) 进化计算 算法 点(几何) 数学 几何学 程序设计语言
作者
Kalyanmoy Deb,Himanshu Jain
出处
期刊:IEEE Transactions on Evolutionary Computation [Institute of Electrical and Electronics Engineers]
卷期号:18 (4): 577-601 被引量:5254
标识
DOI:10.1109/tevc.2013.2281535
摘要

Having developed multiobjective optimization algorithms using evolutionary optimization methods and demonstrated their niche on various practical problems involving mostly two and three objectives, there is now a growing need for developing evolutionary multiobjective optimization (EMO) algorithms for handling many-objective (having four or more objectives) optimization problems. In this paper, we recognize a few recent efforts and discuss a number of viable directions for developing a potential EMO algorithm for solving many-objective optimization problems. Thereafter, we suggest a reference-point-based many-objective evolutionary algorithm following NSGA-II framework (we call it NSGA-III) that emphasizes population members that are nondominated, yet close to a set of supplied reference points. The proposed NSGA-III is applied to a number of many-objective test problems with three to 15 objectives and compared with two versions of a recently suggested EMO algorithm (MOEA/D). While each of the two MOEA/D methods works well on different classes of problems, the proposed NSGA-III is found to produce satisfactory results on all problems considered in this paper. This paper presents results on unconstrained problems, and the sequel paper considers constrained and other specialties in handling many-objective optimization problems.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
余一台完成签到,获得积分10
刚刚
派派发布了新的文献求助10
1秒前
1秒前
最棒哒发布了新的文献求助10
1秒前
wlL发布了新的文献求助10
1秒前
Wee发布了新的文献求助10
1秒前
1秒前
虚心的乐荷完成签到 ,获得积分10
1秒前
Leon应助唠叨的映真采纳,获得10
1秒前
1秒前
爆米花应助Qinjichao采纳,获得10
2秒前
Lm应助谢言一采纳,获得10
4秒前
黄辉冯发布了新的文献求助30
4秒前
4秒前
meimei发布了新的文献求助50
5秒前
5秒前
情怀应助CC采纳,获得10
5秒前
上官若男应助Reset采纳,获得10
5秒前
jzh发布了新的文献求助10
6秒前
NCS完成签到 ,获得积分10
6秒前
加油呀完成签到,获得积分10
6秒前
YiningXu发布了新的文献求助10
6秒前
科研通AI5应助wwwww采纳,获得10
7秒前
不安的未来完成签到,获得积分10
8秒前
Owen应助糊糊采纳,获得10
8秒前
研友_8yNl3L完成签到,获得积分10
9秒前
10秒前
李凡发布了新的文献求助10
11秒前
Orange应助科研通管家采纳,获得10
12秒前
汉堡包应助粗心的怜寒采纳,获得10
12秒前
CAOHOU应助科研通管家采纳,获得10
12秒前
NexusExplorer应助科研通管家采纳,获得10
12秒前
领导范儿应助科研通管家采纳,获得10
12秒前
好好完成签到,获得积分10
12秒前
SYLH应助科研通管家采纳,获得10
12秒前
午后两点最热完成签到 ,获得积分10
12秒前
Jasper应助科研通管家采纳,获得10
12秒前
无花果应助科研通管家采纳,获得10
12秒前
研友_VZG7GZ应助科研通管家采纳,获得10
12秒前
SYLH应助科研通管家采纳,获得10
13秒前
高分求助中
Production Logging: Theoretical and Interpretive Elements 2700
Conference Record, IAS Annual Meeting 1977 1250
Neuromuscular and Electrodiagnostic Medicine Board Review 1000
APA educational psychology handbook, Vol 1: Theories, constructs, and critical issues 700
Walter Gilbert: Selected Works 500
An Annotated Checklist of Dinosaur Species by Continent 500
岡本唐貴自伝的回想画集 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 物理 生物化学 纳米技术 计算机科学 化学工程 内科学 复合材料 物理化学 电极 遗传学 量子力学 基因 冶金 催化作用
热门帖子
关注 科研通微信公众号,转发送积分 3653067
求助须知:如何正确求助?哪些是违规求助? 3217055
关于积分的说明 9715426
捐赠科研通 2924895
什么是DOI,文献DOI怎么找? 1601892
邀请新用户注册赠送积分活动 754743
科研通“疑难数据库(出版商)”最低求助积分说明 733180