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Published in: Artificial Intelligence Review 5/2022

09-01-2022

Information-utilization strengthened equilibrium optimizer

Authors: Xinming Zhang, Qiuying Lin

Published in: Artificial Intelligence Review | Issue 5/2022

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Abstract

Equilibrium Optimizer (EO) is a novel meta-heuristic algorithm proposed in 2020 and it has a unique search mechanism and good optimization performance. To further improve its optimization performance, this paper proposes an Information-utilization Strengthened EO (IS-EO). Firstly, a cross EO (CEO) is constructed under the guidance of the historical individual-best information to strengthen information guiding. Secondly, a Global-best opposition learning CEO (GCEO) is created under the guidance of the global best information to a random individual to further strengthen information guiding. Finally, a differential mutation strategy is incorporated into GCEO to construct IS-EO and strengthen information sharing between individuals. Experimental results on the 65 benchmark functions and the 3 engineering design problems show that IS-EO attains stronger search ability and faster running speed compared with EO and other state-of-the-art comparison algorithms and can solve the engineering problems more effectively.

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Metadata
Title
Information-utilization strengthened equilibrium optimizer
Authors
Xinming Zhang
Qiuying Lin
Publication date
09-01-2022
Publisher
Springer Netherlands
Published in
Artificial Intelligence Review / Issue 5/2022
Print ISSN: 0269-2821
Electronic ISSN: 1573-7462
DOI
https://doi.org/10.1007/s10462-021-10105-0

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