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Convergence Time Analysis for the Multi-objective Counting Ones Problem

机译:多目标计数问题的收敛时间分析

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We propose a multi-objective generalisation for the well known Counting Ones problem, called the Multi-objective Counting Ones (MOCO) function. It is shown that the problem has four qualitative different regions. We have constructed a convergence time model for the Simple Evolutionary Multi-objective Optimiser (SEMO) algorithm. The analysis gives insight in the convergence behaviour in each region of the MOCO problem. The model predicts a l~2 ln l running time, which is confirmed by the experimental runs.
机译:我们为众所周知的计数问题提出了多目标泛化,称为多目标计数(MoCo)功能。结果表明,问题有四个定性不同的地区。我们构建了简单的进化多目标优化器(Semo)算法的收敛时间模型。分析为MOCO问题的每个区域中的收敛行为提供了洞察力。该模型预测了L〜2 LN L的运行时间,由实验运行确认。

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