Cargando…
An Ant Colony Optimization Based on Information Entropy for Constraint Satisfaction Problems
Solving the constraint satisfaction problem (CSP) is to find an assignment of values to variables that satisfies a set of constraints. Ant colony optimization (ACO) is an efficient algorithm for solving CSPs. However, the existing ACO-based algorithms suffer from the constructed assignment with high...
Autores principales: | Guan, Boxin, Zhao, Yuhai, Li, Yuan |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7515295/ https://www.ncbi.nlm.nih.gov/pubmed/33267479 http://dx.doi.org/10.3390/e21080766 |
Ejemplares similares
-
Self-Adjusting Ant Colony Optimization Based on Information Entropy for Detecting Epistatic Interactions
por: Guan, Boxin, et al.
Publicado: (2019) -
Colony entropy—Allocation of goods in ant colonies
por: Greenwald, Efrat, et al.
Publicado: (2019) -
Multi-threshold image segmentation for melanoma based on Kapur’s entropy using enhanced ant colony optimization
por: Yang, Xiao, et al.
Publicado: (2022) -
Link Prediction based on Quantum-Inspired Ant Colony Optimization
por: Cao, Zhiwei, et al.
Publicado: (2018) -
Ant Colony Optimization Algorithm for Continuous Domains Based on Position Distribution Model of Ant Colony Foraging
por: Liu, Liqiang, et al.
Publicado: (2014)