差异进化中的不可行性和结构偏差
Infeasibility and structural bias in Differential Evolution
摘要：
本文深入研究了一系列流行的DE配置，以确定组件负责出现的结构性偏差-最近确定的趋势的算法，更喜欢某些地区的搜索空间的原因直接无关的目标函数值。这种趋势已经在GA和PSO中进行了研究，其中在结构偏差的强度和种群大小之间建立了联系，并突出了这些算法的潜在弱点。对于DE，本研究更进一步，扩展了可以有助于存在结构性偏差的方面的范围，包括算法组件，这通常是被忽视的约束处理技术。各种DE配置都接受了方案的偏差测试。结果表明，触发机制DE中的偏见不同，以前发现的GA和PSO -没有明确的依赖于人口规模存在。DE参数的设置是基于一项单独的研究，该研究本身会导致新研究的有趣方向。总的来说，DE对结构偏差是稳健的-只有DE/当前最佳/1/bin明显有偏差，但这种影响通过使用惩罚约束处理技术得到缓解。
英文摘要：
This paper thoroughly investigates a range of popular DE configurations to identify components responsible for the emergence of structural bias - recently identified tendency of the algorithm to prefer some regions of the search space for reasons directly unrelated to the objective function values. Such tendency was already studied in GA and PSO where a connection was established between the strength of structural bias and population sizes and potential weaknesses of these algorithms was highlighted. For DE, this study goes further and extends the range of aspects that can contribute to presence of structural bias by including algorithmic component which is usually overlooked - constraint handling technique. A wide range of DE configurations were subjected to the protocol for testing for bias. Results suggest that triggering mechanism for the bias in DE differs to the one previously found for GA and PSO - no clear dependency on population size exists. Setting of DE parameters is based on a separate study which on its own leads to interesting directions of new research. Overall, DE turned out to be robust against structural bias - only DE/current-to-best/1/bin is clearly biased but this effect is mitigated by the use of penalty constraint handling technique.
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