Aplicaciones de ciencia de datos al proceso de toma de decisiones en la gestión de empresas de acuicultura

Abstract

Despite of the unprecedented growth experienced by the aquaculture industry in the last years, it is still suffering too much from the complexity of its management processes and the high volatility of its results. This have prompted the realization of this doctoral thesis, which aims to apply different data science techniques to develop new computational models that address the problems of the decision-making process of aquaculture companies. This objective has been addressed following a model of incremental innovation, which starts with the determination of the most important decision criteria in this new context and advances with the sequential development of complex methodologies supported by artificial intelligence techniques in order to optimize the main strategic and operational decisions. From our point of view, the development of these methodologies has not only meant a technical novelty with respect to current decision support systems, but also a significant advance in the results of these in different scenarios.