Generational distance is a measure used in evolutionary algorithms to quantify how different a new generation of solutions is from the previous one. It helps to assess the diversity within a population, which is crucial for maintaining evolutionary progress. By analyzing generational distance, researchers can determine whether their optimization process is converging too quickly or stagnating, allowing for adjustments in strategies to enhance exploration and prevent premature convergence.
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