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Handbook of Memetic Algorithms [electronic resource] /edited by Ferrante Neri, Carlos Cotta, Pablo Moscato.

by Neri, Ferrante [editor.]; Cotta, Carlos [editor.]; Moscato, Pablo [editor.]; SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Studies in Computational Intelligence: 379Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 2012.Description: XXVI, 370 p. online resource.ISBN: 9783642232473.Subject(s): Engineering | Artificial intelligence | Engineering mathematics | Engineering | Appl.Mathematics/Computational Methods of Engineering | Artificial Intelligence (incl. Robotics)DDC classification: 519 Online resources: Click here to access online
Contents:
Part I Foundations -- Part II Methodology -- Part III Applications -- Part IV Epilogue.
In: Springer eBooksSummary: Memetic Algorithms (MAs) are computational intelligence structures combining multiple and various operators in order to address optimization problems.  The combination and interaction amongst operators evolves and promotes the diffusion of the most successful units and generates an algorithmic behavior which can handle complex objective functions and hard fitness landscapes.   “Handbook of Memetic Algorithms” organizes, in a structured way, all the the most important results in the field of MAs since their earliest definition until now.  A broad review including various algorithmic solutions as well as successful applications is included in this book. Each class of optimization problems, such as constrained optimization, multi-objective optimization, continuous vs combinatorial problems, uncertainties, are analysed separately and, for each problem,  memetic recipes for tackling the difficulties are given with some successful examples. Although this book contains chapters written by multiple authors, a great attention has been given by the editors to make it a compact and smooth work which covers all the main areas of computational intelligence optimization. It is not only a necessary read for researchers working in the research area, but also a useful handbook for practitioners and engineers who need to address real-world optimization problems. In addition, the book structure makes it an interesting work also for graduate students and researchers is related fields of mathematics and computer science.  
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Part I Foundations -- Part II Methodology -- Part III Applications -- Part IV Epilogue.

Memetic Algorithms (MAs) are computational intelligence structures combining multiple and various operators in order to address optimization problems.  The combination and interaction amongst operators evolves and promotes the diffusion of the most successful units and generates an algorithmic behavior which can handle complex objective functions and hard fitness landscapes.   “Handbook of Memetic Algorithms” organizes, in a structured way, all the the most important results in the field of MAs since their earliest definition until now.  A broad review including various algorithmic solutions as well as successful applications is included in this book. Each class of optimization problems, such as constrained optimization, multi-objective optimization, continuous vs combinatorial problems, uncertainties, are analysed separately and, for each problem,  memetic recipes for tackling the difficulties are given with some successful examples. Although this book contains chapters written by multiple authors, a great attention has been given by the editors to make it a compact and smooth work which covers all the main areas of computational intelligence optimization. It is not only a necessary read for researchers working in the research area, but also a useful handbook for practitioners and engineers who need to address real-world optimization problems. In addition, the book structure makes it an interesting work also for graduate students and researchers is related fields of mathematics and computer science.  

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