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Combining metaheuristics with mathematical programming and machine learning


SEMINARIO DEL DOCTORADO DE ESTADÍSTICA, OPTIMIZACIÓN Y MATEMÁTICA APLICADA. CURSO 2016-2017

Título: Combining metaheuristics with mathematical programming and machine learning

Ponentes: El-Ghazali Talbi  (University of Lille 1)

Fecha: Martes 11 de abril de 2017 a las 12:30 horas

Lugar: Sala de seminarios, Edificio Torretamarit, Universidad Miguel Hernández (Campus de Elche)

Resumen:

During the last years, interest on hybrid metaheuristics has risen considerably in the field of optimization and machine learning. The best results found for many optimization problems in science and industry are obtained by hybrid optimization algorithms. Combinations of optimization tools such as metaheuristics, mathematical programming, constraint programming and machine learning, have provided very efficient optimization algorithms. Four different types of combinations are considered in this talk: (i) Combining metaheuristics with complementary metaheuristics. (ii) Combining metaheuristics with exact methods from mathematical programming approaches which are mostly used in the operations research community. (iii) Combining metaheuristics with machine learning and data mining techniques.


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