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International Conference on Computer and Information Science

ICIS 2017: Computer and Information Science pp 149–161Cite as

Localization Strategy for Island Model Genetic Algorithm to Preserve Population Diversity

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Part of the book series: Studies in Computational Intelligence ((SCI,volume 719))

Abstract

Years after being firstly introduced by Fraser and remodeled for modern application by Bremermann, genetic algorithm (GA) has a significant progression to solve many kinds of optimization problems. GA also thrives into many variations of models and approaches. Multi-population or island model GA (IMGA) is one of the commonly used GA models. IMGA is a multi-population GA model objected to getting a better result (aimed to get global optimum) by intrinsically preserve its diversity. Localization strategy of IMGA is a new approach which sees an island as a single living environment for its individuals. An island’s characteristic must be different compared to other islands. Operator parameter configuration or even its core engine (algorithm) represents the nature of an island. These differences will incline into different evolution tracks which can be its speed or pattern. Localization strategy for IMGA uses three kinds of single GA core: standard GA, pseudo GA, and informed GA. Localization strategy implements migration protocol and the bias value to control the movement. The experiment results showed that localization strategy for IMGA succeeds to solve 3-SAT with an excellent performance. This brand new approach is also proven to have a high consistency and durability.

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Acknowledgements

This work was supported by Indonesia Endowment Fund for Education (LPDP), a scholarship from Ministry of Finance, Republic of Indonesia. This work was conducted while at Graduate School of Information, Production, and Systems, Waseda University, Japan.

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Authors and Affiliations

  1. Graduate School of IPS, Waseda University, Kitakyushu, Fukuoka, 808-0135, Japan

    Alfian Akbar Gozali & Shigeru Fujimura

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  1. Alfian Akbar Gozali
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  2. Shigeru Fujimura
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Correspondence to Alfian Akbar Gozali or Shigeru Fujimura .

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  1. Software Engineering and Information Technology Institute, Central Michigan University, Mt. Pleasant, MI, USA

    Roger Lee

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Gozali, A.A., Fujimura, S. (2018). Localization Strategy for Island Model Genetic Algorithm to Preserve Population Diversity. In: Lee, R. (eds) Computer and Information Science. ICIS 2017. Studies in Computational Intelligence, vol 719. Springer, Cham. https://doi.org/10.1007/978-3-319-60170-0_11

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  • DOI: https://doi.org/10.1007/978-3-319-60170-0_11

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