Evolutionary Multi-Task Optimization Foundations and Methodologies
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Form:Einzelkauf Download
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Sprache:Englisch
Fr. 213.90
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Produktdetails
Format
Kopierschutz
Nein
Family Sharing
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Erscheinungsdatum
29.03.2023
Verlag
Springer Nature SingaporeSeitenzahl
219 (Printausgabe)
Dateigröße
14210 KB
Sprache
Englisch
EAN
9789811956508
Recently, a novel evolutionary search paradigm, Evolutionary Multi-Task (EMT) optimization, has been proposed in the realm of evolutionary computation. In contrast to traditional evolutionary searches, which solve a single task in a single run, evolutionary multi-tasking algorithm conducts searches concurrently on multiple search spaces corresponding to different tasks or optimization problems,each possessing a unique function landscape. By exploiting the latent synergies among distinct problems, the superior search performance of EMT optimization in terms of solution quality and convergence speed has been demonstrated in a variety of continuous, discrete, and hybrid (mixture of continuous and discrete) tasks.
This book discusses the foundations and methodologies of developing evolutionary multi-tasking algorithms for complex optimization, including in domains characterized by factors such as multiple objectives of interest, high-dimensional search spaces and NP-hardness.
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