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Expected runtimes of a simple evolutionary algorithm for the multi-objective minimum spanning tree problem

机译:多目标最小生成树问题的简单进化算法的预期运行时间

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摘要

Evolutionary algorithms are applied to problems that are not well understood as well as to problems in combinatorial optimization. The analysis of these search heuristics has been started for some well-known polynomial solvable problems. Such analyses are starting points for the analysis of evolutionary algorithms on difficult problems. We present the first runtime analysis of a multi-objective evolutionary algorithm on a NP-hard problem. The subject of our analysis is the multi-objective minimum spanning tree problem for which we give upper bounds on the expected time until a simple evolutionary algorithm has produced a population including for each extremal point of the Pareto front a corresponding spanning tree. These points are of particular interest as they give a 2-approximation of the Pareto front. We show that in expected pseudopolynomial time a population is produced that includes for each extremal point a corresponding spanning tree. (C) 2006 Elsevier B.V. All rights reserved.
机译:进化算法适用于尚未很好理解的问题以及组合优化中的问题。这些搜索启发式方法的分析已经开始用于一些众所周知的多项式可解问题。这样的分析是分析棘手问题的进化算法的起点。我们提出了一个关于NP难问题的多目标进化算法的首次运行时分析。我们的分析主题是多目标最小生成树问题,在此问题上我们给出了预期的时间上限,直到简单的进化算法生成了一个种群,其中包括针对Pareto前沿的每个极值点的对应生成树。这些点特别令人感兴趣,因为它们给出了Pareto前沿的2近似值。我们表明,在预期的伪多项式时间内,会产生一个总体,其中包括每个极值点的对应生成树。 (C)2006 Elsevier B.V.保留所有权利。

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