An improved brain storm optimization with chunking-grouping method

Jinglei Guo; Chen Gao; Shouyong Jiang; Wei Xie; Zhijian Wu

doi:10.1002/cpe.7924

An improved brain storm optimization with chunking-grouping method

Jinglei Guo^* (Corresponding Author), Chen Gao, Shouyong Jiang, Wei Xie^* (Corresponding Author), Zhijian Wu

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

Abstract

Brain storm optimization (BSO) is a population-based intelligence algorithm for optimization problems, which has attracted researchers' growing attention due to its simplicity and efficiency. An improved BSO, called CIBSO, is presented in this article. First of all, a new grouping method, in which the population is partitioned into chunks according to the fitness and recombined to groups, is developed to balance each group with same quality-level. Afterwards, a new mutation strategy is designed in CIBSO and a learning mechanism is used to adaptively select appropriate strategy. Experiments on the CEC2014 test suite indicate that CIBSO is better or at least competitive performance against the compared BSO variants.

Original language	English
Article number	e7924
Number of pages	20
Journal	Concurrency and Computation: Practice and Experience
Volume	36
Issue number	4
Early online date	7 Oct 2023
DOIs	https://doi.org/10.1002/cpe.7924
Publication status	Published - 15 Feb 2024

Bibliographical note

Funding Information:
This work is part funded by the National Natural Science Foundation of China (No. 62377026), and the Fundamental Research Funds for the Central Universities (No. CCNU20TS026).

Data Availability Statement

The data used to support the findings of this investigation is accessible upon request from the corresponding author.

Keywords

brain storm optimization (BSO)
chunking-group
learning mechanism

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Cite this

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An improved brain storm optimization with chunking-grouping method

Abstract

Bibliographical note

Data Availability Statement

Keywords

Access to Document

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