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2018 | OriginalPaper | Chapter

Negative Space-Based Population Initialization Algorithm (NSPIA)

Authors : Krystian Łapa, Krzysztof Cpałka, Andrzej Przybył, Konrad Grzanek

Published in: Artificial Intelligence and Soft Computing

Publisher: Springer International Publishing

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Abstract

There are many different varieties of population-based algorithms. They are interesting techniques for investigating of the search space of solutions and can be used, among others, to solve optimization problems. They usually start from initialization of a population of individuals, each of which encodes parameters of a single solution to the problem under consideration. After initialization, the preselected individuals are processed in a way that depends on the specifics of the algorithm. Therefore, properly implemented population initialization can significantly improve the algorithm’s operation and increase the quality of obtained results. This article describes a new population initialization algorithm. Its characteristic feature is the marginalization of those areas of the search space, in which once localized individuals were assessed as not satisfying. The proposed algorithm is of particular importance for problems in which no information is available that can improve the search procedure (black-box optimization). To test the proposed algorithm simulations were carried out using well-known benchmark functions.

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Title: Negative Space-Based Population Initialization Algorithm (NSPIA)
Authors: Krystian Łapa
Krzysztof Cpałka
Andrzej Przybył
Konrad Grzanek
Publisher: Springer International Publishing
Book: Artificial Intelligence and Soft Computing
Print ISBN: 978-3-319-91252-3

Electronic ISBN: 978-3-319-91253-0

Copyright Year: 2018
DOI: https://doi.org/10.1007/978-3-319-91253-0_42

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