Metaheuristics for pruning convolutional neural networks: A comparative study

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Vikas Palakonda, Jamshid Tursunboev, Jae-Mo Kang, Sunghwan Moon

Published: 2025, Last Modified: 12 Nov 2025Expert Syst. Appl. 2025EveryoneRevisionsBibTeXCC BY-SA 4.0
Abstract: Highlights•This study investigates the application of various metaheuristics to prune CNNs.•The impact of binary, continuous, and integer encodings on pruning CNNs is studied.•The effect of single- and multi-objective formulations on CNN pruning is explored.•Research findings offer critical insights on metaheuristics-based pruning on CNNs.