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EvoMapX: An explainable framework for metaheuristic optimization algorithms
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AI
DOI：10.1016/j.eswa.2025.129514.png)
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Abstract
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• EvoMapX is a novel explainable framework designed to interpret the internal dynamics of population-based optimization algorithms. • EvoMapX includes three interpretable structures: the Operator Attribution Matrix (OAM), the Population Evolution Graph (PEG), and the Convergence Driver Score (CDS). - EvoMapX is evaluated on the CEC 2021 benchmark suite using four widely used metaheuristic methods, providing both graphical and textual insights into algorithm performance and decision-making.
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