[:es]Título: «How machine learning can help optimization»
Ponente: El-ghazali Talbi (Polytech’Lille – University of Lille)
Organizador: Juan Aparicio
Date: Viernes 29 de noviembre a las 11:00 horas.
Lugar: Sala de Seminarios del CIO, Edificio Torretamarit, Universidad Miguel Hernández (Campus de Elche)
Resumen: During the last years, research in applying machine learning (ML) in designing efficient, effective and robust metaheuristics become increasingly popular. Many of those data driven metaheuristics have generated high quality results and represent state-of-the-art optimization algorithms. Although various appproaches have been proposed, there is a lack of a comprehensive survey and taxonomy on this research topic. In this talk we will investigate the different opportunities for using ML into metaheuristics. We define in a unified way the various ways synergies that may be achieved. A detailed taxonomy is proposed according to the concerned search component: target optimization problem, low-level and high-level components of metaheuristics. Our goal is also to motivate researchers in optimization to include ideas from ML into metaheuristics. We identify some open research issues in this topic which needs further in-depth investigations.[:]
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Seminario CIO: Distribution of Profits in Agricultural Supply Chains, A Cooperative Game Theory Approach
Título: Distribution of Profits in Agricultural Supply Chains: A Cooperative Game Theory Approach Ponente: Anjeza Bekolli (Agricultural University of Tirana, Albania) Fecha y hora: 10/06/2024, 12:00 Lugar: Sala de seminarios (CIO) y online Organizador: Ana Meca Martínez Abstract: In this study, our focus is on decentralized agricultural supply chains, where multiple non-competing distributors serve the demand of their respective markets. These [...]