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May, 2023
在噪声存在的情况下多目标进化算法的运行分析
Runtime Analyses of Multi-Objective Evolutionary Algorithms in the Presence of Noise
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Matthieu Dinot, Benjamin Doerr, Ulysse Hennebelle, Sebastian Will
TL;DR
通过数学运行分析一个简单的多目标进化算法(MOEA)在评估函数噪声存在的情况下对模拟基准的第一次 Pareto 前沿的发现表明,MOEA的稳健性源于其隐式多样性机制,该机制旨在使其能够计算涵盖整个 Pareto 前沿的人口。
Abstract
In single-objective optimization, it is well known that
evolutionary algorithms
also without further adjustments can tolerate a certain amount of
noise
in the evaluation of the objective function. In contrast, th
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