Tekijä: Mike Preuss (ed.); Michael G. Epitropakis (ed.); Xiaodong Li (ed.); Jonathan E. Fieldsend (ed.) Kustantaja: Springer (2021) Saatavuus: Noin 17-20 arkipäivää
Tekijä: Mike Preuss (ed.); Michael G. Epitropakis (ed.); Xiaodong Li (ed.); Jonathan E. Fieldsend (ed.) Kustantaja: Springer (2022) Saatavuus: Noin 17-20 arkipäivää
Tekijä: Thomas Bartz-Beielstein; Marco Chiarandini; Luís Paquete; Mike Preuss Kustantaja: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG (2010) Saatavuus: Noin 17-20 arkipäivää
Tekijä: Thomas Bartz-Beielstein; Marco Chiarandini; Luís Paquete; Mike Preuss Kustantaja: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG (2014) Saatavuus: Noin 17-20 arkipäivää
Tekijä: Christian Grimme; Mike Preuss; Frank W. Takes; Annie Waldherr Kustantaja: Springer Nature Switzerland AG (2020) Saatavuus: Noin 17-20 arkipäivää
Tekijä: Thomas Bäck; Mike Preuss; André Deutz; Hao Wang; Carola Doerr; Michael Emmerich; Heike Trautmann Kustantaja: Springer Nature Switzerland AG (2020) Saatavuus: Noin 17-20 arkipäivää
Tekijä: Thomas Bäck (ed.); Mike Preuss (ed.); André Deutz (ed.); Hao Wang (ed.); Carola Doerr (ed.); Michael Emmerich (ed.); Traut Kustantaja: Springer (2020) Saatavuus: Noin 17-20 arkipäivää
Tekijä: Max van Duijn; Mike Preuss; Viktoria Spaiser; Frank Takes; Suzan Verberne Kustantaja: Springer Nature Switzerland AG (2020) Saatavuus: Noin 17-20 arkipäivää
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.
