Self-Adaptive Differential Evolution Hyper-Heuristic with Applications in Process Design



Document title: Self-Adaptive Differential Evolution Hyper-Heuristic with Applications in Process Design
Journal: Computación y sistemas
Database: PERIÓDICA
System number: 000410017
ISSN: 1405-5546
Authors: 1
1
2
Institutions: 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
Year:
Season: Abr-Jun
Volumen: 20
Number: 2
Pages: 173-193
Country: México
Language: Inglés
Document type: Artículo
Approach: Experimental, aplicado
English 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
Disciplines: Ciencias de la computación
Keyword: 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
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