Late parallelization and feedback approaches for distributed computation of evolutionary multi-objective optimization algorithms

Distributing of the multi-objective evolutionary algorithms into various computational devices in a parallel fashion is a method for speeding up the execution time of the algorithms. When the processors are increased in number, the gain from parallelization decreases. For this reason, the aim of the...

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Vydáno v:	Neural computing & applications Ročník 30; číslo 3; s. 723 - 733
Hlavní autoři:	Altinoz, O. Tolga, Deb, Kalyanmoy
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	London Springer London 01.08.2018 Springer Nature B.V
Témata:	Algorithms Artificial Intelligence Computation Computational Biology/Bioinformatics Computational Science and Engineering Computer Science Data Mining and Knowledge Discovery Double cusps Evolutionary algorithms Feedback Image Processing and Computer Vision Iscmi15 Multiple objective analysis Parallel processing Population (statistical) Probability and Statistics in Computer Science Processors Reference point-based NSGA-II Parallelization Distributing computing
ISSN:	0941-0643, 1433-3058
On-line přístup:	Získat plný text
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