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arXiv 0901.4146cond-mat.dis-nn
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一维幂律相互作用自旋玻璃的进化算法分析

Analysis of Evolutionary Algorithms on the One-Dimensional Spin Glass with Power-Law Interactions

Martin Pelikan, Helmut G. Katzgraber

摘要:

本文针对具有幂律相互作用的一维自旋玻璃模型,对几种进化算法进行了深入的实证分析。所考虑的自旋玻璃模型提供了一种机制,用于调整相互作用的有效范围,这使得问题有趣的算法基准。作为算法,本文考虑了两点均匀交叉的遗传算法(GA)和分层贝叶斯优化算法(hBOA)。hBOA的表现优于GA的两种变体,而均匀交叉的GA表现最差。比较算法之间的差异变得更加显着的问题大小的增长和范围的相互作用减少。与均匀交叉的GA不同,对于hBOA和两点交叉的GA,具有短程相互作用的实例被证明是更容易的。本文还指出了未来研究的有趣途径。

英文摘要:

This paper provides an in-depth empirical analysis of several evolutionary algorithms on the one-dimensional spin glass model with power-law interactions. The considered spin glass model provides a mechanism for tuning the effective range of interactions, what makes the problem interesting as an algorithm benchmark. As algorithms, the paper considers the genetic algorithm (GA) with twopoint and uniform crossover, and the hierarchical Bayesian optimization algorithm (hBOA). hBOA is shown to outperform both variants of GA, whereas GA with uniform crossover is shown to perform worst. The differences between the compared algorithms become more significant as the problem size grows and as the range of interactions decreases. Unlike for GA with uniform crossover, for hBOA and GA with twopoint crossover, instances with short-range interactions are shown to be easier. The paper also points out interesting avenues for future research.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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