 Название: Advances in Metaheuristics Algorithms: Methods and Applications
Автор: Erik Cuevas, Daniel Zald?var, Marco P?rez-Cisneros
Издательство: Springer International Publishing
Год: 2018
ISBN: 9783319893099
Серия: Studies in Computational Intelligence (Book 775)
Формат: epub, pdf
Страниц: XIV, 218
Размер: 13,9 mb
Язык: English
This book explores new alternative metaheuristic developments that have proved to be effective in their application to several complex problems. Though most of the new metaheuristic algorithms considered offer promising results, they are nevertheless still in their infancy. To grow and attain their full potential, new metaheuristic methods must be applied in a great variety of problems and contexts, so that they not only perform well in their reported sets of optimization problems, but also in new complex formulations. The only way to accomplish this is to disseminate these methods in various technical areas as optimization tools. In general, once a scientist, engineer or practitioner recognizes a problem as a particular instance of a more generic class, he/she can select one of several metaheuristic algorithms that guarantee an expected optimization performance. Unfortunately, the set of options are concentrated on algorithms whose popularity and high proliferation outstrip those of the new developments. This structure is important, because the authors recognize this methodology as the best way to help researchers, lecturers, engineers and practitioners solve their own optimization problems.
Introduction
Cuevas, Erik (et al.)
Pages 1-8
The Metaheuristic Algorithm of the Social-Spider
Cuevas, Erik (et al.)
Pages 9-33
Calibration of Fractional Fuzzy Controllers by Using the Social-Spider Method
Cuevas, Erik (et al.)
Pages 35-55
The Metaheuristic Algorithm of the Locust-Search
Cuevas, Erik (et al.)
Pages 57-76
Identification of Fractional Chaotic Systems by Using the Locust Search Algorithm
Cuevas, Erik (et al.)
Pages 77-92
The States of Matter Search (SMS)
Cuevas, Erik (et al.)
Pages 93-118
Multimodal States of Matter Search
Cuevas, Erik (et al.)
Pages 119-165
Metaheuristic Algorithms Based on Fuzzy Logic
Cuevas, Erik (et al.)
Pages 167-218
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Advances in Metaheuristics Algorithms: Methods and Applications 
