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2015 | OriginalPaper | Chapter

Large-Scale Global Optimization Using Dynamic Population-Based DE

Authors : Seema Chauhan, Suman Banerjee, Nanda Dulal Jana

Published in: Intelligent Computing and Applications

Publisher: Springer India

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Abstract

Large-scale global optimization is one of the most challenging problems in the domain of stochastic optimization. Due to high dimensionality in the entire optimization process, different types of problems may occur for finding the global optima, e.g., solution space increases exponentially, problem complexity increases, and candidate search direction also increases exponentially. So, deterministic optimization algorithms cannot perform well for this kind of problems. Differential evolutionary algorithm is a population-based, stochastic search and optimization algorithm which can be used for global optimization problems. In this paper, we present self-adaptive dynamic population-based differential evolutionary algorithm which automatically adapts its parameters including population size.

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Metadata
Title
Large-Scale Global Optimization Using Dynamic Population-Based DE
Authors
Seema Chauhan
Suman Banerjee
Nanda Dulal Jana
Copyright Year
2015
Publisher
Springer India
Book
Intelligent Computing and Applications

Print ISBN: 978-81-322-2267-5

Electronic ISBN: 978-81-322-2268-2

Copyright Year: 2015

DOI
https://doi.org/10.1007/978-81-322-2268-2_27

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