南方科技大学知识苑(SUSTech KC): Decomposition gradient descent method for bi-objective optimisation

题名	Decomposition gradient descent method for bi-objective optimisation
作者	Chen，Jingjing 1; Li，Genghui2 ; Lin，Xi 2
通讯作者	Chen，Jingjing
发表日期	2024-01-22
DOI	10.1504/IJBIC.2024.136218
发表期刊	International Journal of Bio-Inspired Computation 影响因子和分区
ISSN	1758-0366
EISSN	1758-0374
卷号	23 期号:1页码:28-38
摘要	Population-based decomposition methods decompose a multi-objective optimisation problem (MOP) into a set of single-objective subproblems (SOPs) and then solve them collaboratively to produce a set of Pareto optimal solutions. Most of these methods use heuristics such as genetic algorithms as their search engines. As a result, these methods are not very efficient. This paper investigates how to do a gradient search in multi-objective decomposition methods. We use the NBI-style Tchebycheff method to decompose a MOP since it is not sensitive to the scales of objectives. However, since the objectives of the resultant SOPs are non-differentiable, they cannot be directly optimised by the classical gradient methods. We propose a new gradient descent method, decomposition gradient descent (DGD), to optimise them. We study its convergence property and conduct numerical experiments to show its efficiency.
关键词	decomposition strategy gradient descent method multi-objective optimisation NBI-style Tchebycheff method
相关链接	[Scopus记录]
收录类别	EI
语种	英语
学校署名	其他
EI入藏号	20240515476410
EI主题词	Genetic algorithms ; Gradient methods ; Heuristic methods ; Pareto principle ; Search engines
EI分类号	Computer Software, Data Handling and Applications:723 ; Optimization Techniques:921.5 ; Numerical Methods:921.6
Scopus记录号	2-s2.0-85183575339
来源库	Scopus
引用统计	被引频次[WOS]：1
成果类型	期刊论文
条目标识符	http://sustech.caswiz.com/handle/2SGJ60CL/701547
专题	工学院_系统设计与智能制造学院
作者单位	1.Department of Computer Science,City University of Hong Kong,Hong Kong 2.School of System Design and Intelligent Manufacturing,Southern University of Science and Technology,Shenzhen,518055,China
推荐引用方式 GB/T 7714	Chen，Jingjing,Li，Genghui,Lin，Xi. Decomposition gradient descent method for bi-objective optimisation[J]. International Journal of Bio-Inspired Computation,2024,23(1):28-38.
APA	Chen，Jingjing,Li，Genghui,&Lin，Xi.(2024).Decomposition gradient descent method for bi-objective optimisation.International Journal of Bio-Inspired Computation,23(1),28-38.
MLA	Chen，Jingjing,et al."Decomposition gradient descent method for bi-objective optimisation".International Journal of Bio-Inspired Computation 23.1(2024):28-38.