| Revista: | Computación y sistemas |
| Base de datos: | PERIÓDICA |
| Número de sistema: | 000410017 |
| ISSN: | 1405-5546 |
| Autores: | Peraza Vázquez, Hernán1 Torres Huerta, Aidé M1 Flores Vela, Abelardo2 |
| Instituciones: | 1Instituto Politécnico Nacional, Centro de Investigación en Ciencia Aplicada y Tecnología Avanzada, Altamira, Tamaulipas. México 2Instituto Politécnico Nacional, Centro Mexicano para la Producción más Limpia, Ciudad de México. México |
| Año: | 2016 |
| Periodo: | Abr-Jun |
| Volumen: | 20 |
| Número: | 2 |
| Paginación: | 173-193 |
| País: | México |
| Idioma: | Inglés |
| Tipo de documento: | Artículo |
| Enfoque: | Experimental, aplicado |
| Resumen en inglés | The paper presents a differential evolution (DE)-based hyper-heuristic algorithm suitable for the optimization of mixed-integer non-linear programming (MINLP) problems. The hyper-heuristic framework includes self-adaptive parameters, an ε-constrained method for handling constraints, and 18 DE variants as low-level heuristics. Using the proposed approach, we solved a set of classical test problems on process synthesis and design and compared the results with those of several state-of-the-art evolutionary algorithms. To verify the consistency of the proposed approach, the above-mentioned comparison was made with respect to the percentage of convergences to the global optimum (NRC) and the average number of objective function evaluations (NFE) over several trials. Thus, we found that the proposed methodology significantly improves performance in terms of NRC and NFE |
| Disciplinas: | Ciencias de la computación |
| Palabras clave: | Programación, Síntesis de procesos, Programación mixta entera no lineal, Evolución diferencial, Algoritmos, Hiper-heurística |
| Keyword: | Computer science, Programming, Processes synthesis, Mixed-integer nonlinear programming, Differential evolution, Algorithms, Hyper-heuristics |
| Texto completo: | Texto completo (Ver HTML) |
