Servicios Personalizados
Revista
Articulo
Indicadores
- Citado por SciELO
- Accesos
Links relacionados
- Similares en SciELO
Compartir
Computación y Sistemas
versión On-line ISSN 2007-9737versión impresa ISSN 1405-5546
Resumen
PERAZA-VAZQUEZ, Hernán; TORRES-HUERTA, Aidé M. y FLORES-VELA, Abelardo. Self-Adaptive Differential Evolution Hyper-Heuristic with Applications in Process Design. Comp. y Sist. [online]. 2016, vol.20, n.2, pp.173-193. ISSN 2007-9737. https://doi.org/10.13053/cys-20-2-2334.
Abstract. 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.
Palabras llave : Processes synthesis; mixed-integer nonlinear programming (MINLP) problems; differential evolution (DE); hyper-heuristics.