Hybridization of Bio-inspired Metaheuristics for Global Optimisation - Elkhechafi, Mariam;Hachimi, Hanaa;Elkettani, Youssfi
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This book explains the recent problems concerning the solving of Optimization models. We present the methods for solving them and their applications. In the first part of this book we present the new original metaheuristics shown for the first time in the course of our book project, methods which we have developed, based on the principle of hybridization. We show that these last algorithm obtain greater precision results, compared with the older metaheuristics. Secondly, concerning the multi-objective modeling, we present our new method developed for evaluating water quality in the Sebou…mehr

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Produktbeschreibung
This book explains the recent problems concerning the solving of Optimization models. We present the methods for solving them and their applications. In the first part of this book we present the new original metaheuristics shown for the first time in the course of our book project, methods which we have developed, based on the principle of hybridization. We show that these last algorithm obtain greater precision results, compared with the older metaheuristics. Secondly, concerning the multi-objective modeling, we present our new method developed for evaluating water quality in the Sebou region of Morocco. Keywords : Optimization, Metaheuristic algorithms, Hybridization.
Autorenporträt
Mariam Elkhechafi, Ph.D Candidate in Applied Mathematics & ComputerScience, I¿m a temporary teacher and researcherat the Ibn Tofail University. My research areas are as follows:Statistical processing and analysis of data, Optimization, Bio-inspired Metaheuristic.