![](/images/graphics-bg.png)
A Multiobjective Brain Storm Optimization Algorithm Based on Decomposition
Joint Authors
Source
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-01-22
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
Brain storm optimization (BSO) algorithm is a simple and effective evolutionary algorithm.
Some multiobjective brain storm optimization algorithms have low search efficiency.
This paper combines the decomposition technology and multiobjective brain storm optimization algorithm (MBSO/D) to improve the search efficiency.
Given weight vectors transform a multiobjective optimization problem into a series of subproblems.
The decomposition technology determines the neighboring clusters of each cluster.
Solutions of adjacent clusters generate new solutions to update population.
An adaptive selection strategy is used to balance exploration and exploitation.
Besides, MBSO/D compares with three efficient state-of-the-art algorithms, e.g., NSGAII and MOEA/D, on twenty-two test problems.
The experimental results show that MBSO/D is more efficient than compared algorithms and can improve the search efficiency for most test problems.
American Psychological Association (APA)
Dai, Cai& Lei, Xiujuan. 2019. A Multiobjective Brain Storm Optimization Algorithm Based on Decomposition. Complexity،Vol. 2019, no. 2019, pp.1-11.
https://search.emarefa.net/detail/BIM-1132072
Modern Language Association (MLA)
Dai, Cai& Lei, Xiujuan. A Multiobjective Brain Storm Optimization Algorithm Based on Decomposition. Complexity No. 2019 (2019), pp.1-11.
https://search.emarefa.net/detail/BIM-1132072
American Medical Association (AMA)
Dai, Cai& Lei, Xiujuan. A Multiobjective Brain Storm Optimization Algorithm Based on Decomposition. Complexity. 2019. Vol. 2019, no. 2019, pp.1-11.
https://search.emarefa.net/detail/BIM-1132072
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1132072