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1. |
Record Nr. |
UNINA9910149037003321 |
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Autore |
Hill Grace Livingston |
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Titolo |
The girl from Montana / / Grace Livingston Hill |
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Pubbl/distr/stampa |
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[Auckland, New Zealand] : , : The Floating Press, , 2015 |
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©2015 |
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ISBN |
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Descrizione fisica |
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1 online resource (218 pages) |
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Disciplina |
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Soggetti |
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Christian fiction, American |
English fiction - 20th century |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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2. |
Record Nr. |
UNINA9910734094603321 |
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Autore |
Preuss Mike |
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Titolo |
Multimodal Optimization by Means of Evolutionary Algorithms / / by Mike Preuss |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015 |
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ISBN |
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Edizione |
[1st ed. 2015.] |
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Descrizione fisica |
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1 online resource (206 p.) |
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Collana |
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Natural Computing Series, , 2627-6461 |
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Disciplina |
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Soggetti |
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Algorithms |
Computational intelligence |
Mathematical optimization |
Computational Intelligence |
Optimization |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Description based upon print version of record. |
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Nota di bibliografia |
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Includes bibliographical references. |
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Nota di contenuto |
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Introduction: Towards Multimodal Optimization -- Experimentation in Evolutionary Computation -- Groundwork for Niching -- Nearest-Better Clustering -- Niching Methods and Multimodal Optimization Performance -- Nearest-Better Based Niching. |
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Sommario/riassunto |
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This book offers the first comprehensive taxonomy for multimodal optimization algorithms, work with its root in topics such as niching, parallel evolutionary algorithms, and global optimization. The author explains niching in evolutionary algorithms and its benefits; he examines their suitability for use as diagnostic tools for experimental analysis, especially for detecting problem (type) properties; and he measures and compares the performances of niching and canonical EAs using different benchmark test problem sets. His work consolidates the recent successes in this domain, presenting and explaining use cases, algorithms, and performance measures, with a focus throughout on the goals of the optimization processes and a deep understanding of the algorithms used. The book will be useful for researchers and practitioners in the area of computational intelligence, particularly those engaged with heuristic search, multimodal optimization, evolutionary computing, and experimental analysis. |
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