Improving the Quantum Multi-Swarm Optimization with Adaptive Differential Evolution for Dynamic Environments

Improving the Quantum Multi-Swarm Optimization with Adaptive Differential Evolution for Dynamic Environments

In this study, the modification of the quantum multi-swarm optimization algorithm is proposed for dynamic optimization problems. The modification implies using the search operators from differential evolution algorithm with a certain probability within particle swarm optimization to improve the algo...

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Bibliographic Details
Main Authors: Vladimir Stanovov, Shakhnaz Akhmedova, Aleksei Vakhnin, Evgenii Sopov, Eugene Semenkin, Michael Affenzeller
Format: Article
Language:English
Published: MDPI AG 2022-04-01
Series:Algorithms
Subjects:
dynamic environments
differential evolution
particle swarm optimization
evolutionary algorithms
Online Access:https://www.mdpi.com/1999-4893/15/5/154

Internet

https://www.mdpi.com/1999-4893/15/5/154

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