| Revista: | Polibits |
| Base de datos: | PERIÓDICA |
| Número de sistema: | 000383480 |
| ISSN: | 1870-9044 |
| Autores: | Andre, Leanderson1 Parpinelli, Rafael Stubs1 |
| Instituciones: | 1Universidade para o Desenvolvimento do Estado de Santa Catarina, Departamento de Ciencias da Computacao, Joinville, Santa Catarina. Brasil |
| Año: | 2015 |
| Periodo: | Ene-Jun |
| Número: | 51 |
| Paginación: | 47-54 |
| País: | México |
| Idioma: | Inglés |
| Tipo de documento: | Artículo |
| Enfoque: | Aplicado, descriptivo |
| Resumen en inglés | In this paper the well-known 0-1 Multiple Knapsack Problem (MKP) is approached by an adaptive Binary Differential Evolution (ABDE) algorithm. The MKP is a NP-hard optimization problem and the aim is to maximize the total profit subjected to the total weight in each knapsack that must be less than or equal to a given limit. The ABDE self adjusts two parameters, perturbation and mutation rates, using a linear adaptation procedure that changes their probabilities at each generation. Results were obtained using 11 instances of the problem with different degrees of complexity. The results were compared using aBDE, BDE, a standard Genetic Algorithm (GA) and its adaptive version (AGA), and an island-inspired Genetic Algorithm (IGA) and its adaptive version (AIGA). The results show that ABDE obtained better results than the other algorithms. This indicates that the proposed approach is an interesting and a promising strategy to control the parameters and for optimization of complex problems |
| Disciplinas: | Ciencias de la computación, Matemáticas |
| Palabras clave: | Matemáticas aplicadas, Computación evolutiva, Problema de la mochila, Control adaptativo, Evolución diferencial, Algoritmos |
| Keyword: | Computer science, Mathematics, Applied mathematics, Evolutionary computation, Knapsack problem, Adaptive control, Differential evolution, Algorithms |
| Texto completo: | Texto completo (Ver HTML) |
