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Erschienen in:
2021 | OriginalPaper | Buchkapitel
Improvement of Island Genetic Algorithm Using Multiple Fitness Functions
verfasst von : Shigeka Nakajima, Masami Takata
Erschienen in: Advances in Parallel & Distributed Processing, and Applications
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Abstract
In this paper, we propose an island genetic algorithm (GA) that promotes a unique evolution. In a conventional island GA [3], all objective functions are combined into a single fitness function. Hence, offspring generations are generated using the same fitness function. In the natural world, each should evolve in a manner that suits the environment, and owing to the various environments on Earth, various organisms have been diversified. Therefore, we propose an improved island GA with different fitness functions to create a distinctive evolution.