A novel binary particle swarm optimization
By M. A. Khanesar, M. Teshnehlab, M. A. Shoorehdeli. Mediterranean Conference on Control and Automation, 2007
440 citations recorded by the source corpus.
Particle swarm optimization (PSO) as a novel computational intelligence technique, has succeeded in many continuous problems. But in discrete or binary version there are still some difficulties. In this paper a novel binary PSO is proposed. This algorithm proposes a new definition for the velocity vector of binary PSO. It will be shown that this algorithm is a better interpretation of continuous PSO into discrete PSO than the older versions. Also a number of benchmark optimization problems are solved using this concept and quite satisfactory results are obtained.
Subfields: Artificial Intelligence, Control and Systems Engineering
View Paper: https://www.semanticscholar.org/paper/d434701707a6c5afe725f13dd13f57fb995dea4d
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In Artificial Intelligence
In Control and Systems Engineering
Citations in the corpus
- Particle swarm optimisation for feature selection in classification: Novel initialisation and updating mechanisms (2014, methodology): “Feature selection is a binary problem, but continuous PSO is used in this work because there are some limitations in the current version of binary PSO [43].”