A Diversity Model Based on Dimension Entropy and Its Application to Swarm Intelligence Algorithm

A Diversity Model Based on Dimension Entropy and Its Application to Swarm Intelligence Algorithm

The swarm intelligence algorithm has become an important method to solve optimization problems because of its excellent self-organization, self-adaptation, and self-learning characteristics. However, when a traditional swarm intelligence algorithm faces high and complex multi-peak problems, populati...

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Bibliographic Details
Published in:Entropy (Basel, Switzerland) Vol. 23; no. 4; p. 397
Main Authors: Kang, Hongwei, Bei, Fengfan, Shen, Yong, Sun, Xingping, Chen, Qingyi
Format: Journal Article
Language:English
Published: Switzerland MDPI AG 27-03-2021
MDPI
Subjects:
Algorithms
Convergence
dimension entropy
diversity model
Entropy
Genetic algorithms
Information systems
Machine learning
Methods
Optimization
Optimization algorithms
Population
Swarm intelligence
swarm intelligence algorithm
dimension entropy
diversity model
swarm intelligence algorithm
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Summary:The swarm intelligence algorithm has become an important method to solve optimization problems because of its excellent self-organization, self-adaptation, and self-learning characteristics. However, when a traditional swarm intelligence algorithm faces high and complex multi-peak problems, population diversity is quickly lost, which leads to the premature convergence of the algorithm. In order to solve this problem, dimension entropy is proposed as a measure of population diversity, and a diversity control mechanism is proposed to guide the updating of the swarm intelligence algorithm. It maintains the diversity of the algorithm in the early stage and ensures the convergence of the algorithm in the later stage. Experimental results show that the performance of the improved algorithm is better than that of the original algorithm.
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content type line 23
ISSN:1099-4300
1099-4300
DOI:10.3390/e23040397