| Revue: | Computación y sistemas |
| Base de datos: | PERIÓDICA |
| Número de sistema: | 000408048 |
| ISSN: | 1405-5546 |
| Autores: | Kumar, Ajit1 Kumar, Dharmender2 Jarial, S.K1 |
| Instituciones: | 1Deenbandhu Chhotu Ram University of Science and Technology, Sonipat, Haryana. India 2Guru Jambheshwar University of Science and Technology, Hisar, Haryana. India |
| Año: | 2016 |
| Periodo: | Ene-Mar |
| Volumen: | 20 |
| Número: | 1 |
| Paginación: | 55-66 |
| País: | México |
| Idioma: | Inglés |
| Tipo de documento: | Artículo |
| Enfoque: | Analítico |
| Resumen en inglés | The Artificial Bee Colony (ABC) algorithm is a popular swarm based algorithm inspired by the intelligent foraging behavior of honey bees. In the past, many swarm intelligence based techniques were introduced and proved their effective performance in solving various optimization problems. The exploitation of food sources is performed by onlooker bees in accordance with a proportional selection scheme that can be further modified to avoid such shortcomings as population diversity and premature convergence. In this paper, different selection schemes, namely, tournament selection, truncation selection, disruptive selection, linear dynamic scaling, linear ranking, sigma truncation, and exponential ranking have been used to analyze the performance of the ABC algorithm by testing on standard benchmark functions. From the simulation results, the schemes other than the standard ABC prove their efficient performance |
| Disciplinas: | Ciencias de la computación, Matemáticas |
| Palabras clave: | Inteligencia artificial, Matemáticas aplicadas, Inteligencia de enjambre, Algoritmo de colonia artificial de abejas, Optimización |
| Keyword: | Computer science, Mathematics, Artificial intelligence, Applied mathematics, Swarm intelligence, Artificial bee colony algorithm, Optimization |
| Texte intégral: | Texto completo (Ver PDF) |
