An improved brain storm optimization with chunking‐grouping method

Author:

Guo Jinglei1ORCID,Gao Chen1,Jiang Shouyong2,Xie Wei1,Wu Zhijian3

Affiliation:

1. School of Computer Science Central China Normal University Wuhan China

2. Department of Computer Science University of Aberdeen Aberdeen UK

3. School of Computer Science Wuhan University Wuhan China

Abstract

SummaryBrain 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.

Funder

National Natural Science Foundation of China

Fundamental Research Funds for the Central Universities

Publisher

Wiley

Subject

Computational Theory and Mathematics,Computer Networks and Communications,Computer Science Applications,Theoretical Computer Science,Software

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