Advances in Metaheuristics Algorithms: Methods and Applications: 775 (Studies in Computational Intelligence) - Tapa dura

Cuevas, Erik; Zald�var, Daniel; P�rez-Cisneros, Marco

9783319893082: Advances in Metaheuristics Algorithms: Methods and Applications: 775 (Studies in Computational Intelligence)

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ISBN 10: 3319893084 ISBN 13: 9783319893082

Editorial: Springer, 2018

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<DIV>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.<BR></DIV>

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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.

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EditorialSpringer
A�o de publicaci�n2018
ISBN 10 3319893084
ISBN 13 9783319893082
Encuadernaci�nTapa dura
IdiomaIngl�s
N�mero de edici�n1
N�mero de p�ginas234

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9783030077365: Advances in Metaheuristics Algorithms: Methods and Applications: 775 (Studies in Computational Intelligence)

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Advances in Metaheuristics Algorithms. Methods and Applications.

Cuevas, E. et al (Eds.):

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ISBN 10: 3319893084 ISBN 13: 9783319893082

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xiv, 218 p. Hardcover. Versand aus Deutschland / We dispatch from Germany via Air Mail. Einband besto�en, daher M�ngelexemplar gestempelt, sonst sehr guter Zustand. Imperfect copy due to slightly bumped cover, apart from this in very good condition. Stamped. Sprache: Englisch. N� de ref. del art�culo: 34275AB

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Advances in Metaheuristics Algorithms: Methods and Applications (Studies in Computational Intelligence, 775)

Cuevas, Erik; Zald�var, Daniel; P�rez-Cisneros, Marco

Publicado por Springer, 2018

ISBN 10: 3319893084 ISBN 13: 9783319893082

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Advances in Metaheuristics Algorithms: Methods and Applications

Erik Cuevas

Publicado por Springer International Publishing Apr 2018, 2018

ISBN 10: 3319893084 ISBN 13: 9783319893082

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Buch. Condici�n: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 232 pp. Englisch. N� de ref. del art�culo: 9783319893082

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Advances in Metaheuristics Algorithms: Methods and Applications (Studies in Computational Intelligence, 775)

Cuevas, Erik; Zald�var, Daniel; P�rez-Cisneros, Marco

Publicado por Springer, 2018

ISBN 10: 3319893084 ISBN 13: 9783319893082

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Advances in Metaheuristics Algorithms: Methods and Applications

Erik Cuevas

Publicado por Springer International Publishing, 2018

ISBN 10: 3319893084 ISBN 13: 9783319893082

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Buch. Condici�n: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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 thoseof 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. N� de ref. del art�culo: 9783319893082

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Advances in Metaheuristics Algorithms: Methods and Applications

Erik Cuevas|Daniel Zald�var|Marco P�rez-Cisneros

Publicado por Springer International Publishing, 2018

ISBN 10: 3319893084 ISBN 13: 9783319893082

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Condici�n: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Discusses new alternative metaheuristic developments that have proven to be effective in their application to several complex problems&nbspHelps researchers, lecturers, engineers, and practitioners solve their own optimization pr. N� de ref. del art�culo: 448762187

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