H
Hai-Lin Liu
Researcher at Guangdong University of Technology
Publications - 124
Citations - 2635
Hai-Lin Liu is an academic researcher from Guangdong University of Technology. The author has contributed to research in topics: Evolutionary algorithm & Multi-objective optimization. The author has an hindex of 20, co-authored 111 publications receiving 1883 citations.
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Journal ArticleDOI
Decomposition of a Multiobjective Optimization Problem Into a Number of Simple Multiobjective Subproblems
TL;DR: This letter argues that population diversity is more important than convergence in multiobjective evolutionary algorithms for dealing with some MOPs and proposes MOEA/D-M2M, a new version of multiobjectives optimization evolutionary algorithm-based decomposition.
Proceedings ArticleDOI
A modified brain storm optimization
TL;DR: Two novel designs to enhance the conventional BSO performance are proposed and the contributions of SGM and IDS are investigated to show how and why MBSO can perform better than BSO.
Journal ArticleDOI
Adaptively Allocating Search Effort in Challenging Many-Objective Optimization Problems
TL;DR: A new adaptive search effort allocation strategy for multiobjective evolutionary algorithm based on decomposition MOEA/D-M2M, a recent MOEA-D algorithm for challenging MaOPs, that adaptively adjusts the subregions of its subproblems by detecting the importance of different objectives in an adaptive manner.
Journal Article
A multiobjective evolutionary algorithm using dynamic weight design method
TL;DR: A dynamic weight design method based on the projection of the current nondominant solutions and equidistant interpolation is proposed and it is shown that this method can dramatically improve the performance of the algorithms.
Proceedings ArticleDOI
The multiobjective evolutionary algorithm based on determined weight and sub-regional search
Hai-Lin Liu,Xueqiang Li +1 more
TL;DR: This paper presents a kind of easy technology dealing with the constraint, which makes the proposed algorithm solved unconstrained multiobjective problems can also be used to solve constrained multi objective problems.