Expanded Summary of Adaptive Fuzzy Fitness Granulation
Sep 1, 2015·
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1 min read
Mohsen Davarynejad
Mohsen Davarynejad
Image credit: Unsplash
Abstract
Adaptive Fuzzy Fitness Granulation (AFFG) is an advanced optimization technique designed to enhance the performance of evolutionary algorithms (EAs) by integrating fuzzy logic principles into the fitness evaluation process. Traditional EAs rely on precise fitness values to guide the search for optimal solutions, which can be computationally expensive and sometimes lead to premature convergence. AFFG addresses these challenges by introducing a fuzzy granulation mechanism that adaptively adjusts the resolution of fitness evaluations based on the evolutionary process.
Type
Publication
International Journal of Approximate Reasoning, Volume 49, Issue 3.
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