论文标题
停滞检测符合快速突变
Stagnation Detection Meets Fast Mutation
论文作者
论文摘要
最近提出了两种机制，可以通过突变显着加快发现远处改善溶液的加速，即使用从重尾分布中得出的随机突变率（“快速突变”，Doerr等人（2017）），并提高了基于停滞检测的突变强度（Rajabi和Witt和Witt（Rajabi和Witt（2020202020）））。尽管后者可以在给定距离内找到单个所需溶液的渐近最佳可能性，但前者更强大，并且当许多在某种距离内改善解决方案时，性能要好得多。 在这项工作中，我们提出了一种结合两种机制思想的突变策略。我们表明，它还可以获得找到单个远处解决方案的最佳可能性。但是，当存在几种改进的解决方案时，它可以胜过停滞检测方法和快速突变。新运营商不仅仅是前一个机制的交错，而且还优于任何这种交错。
Two mechanisms have recently been proposed that can significantly speed up finding distant improving solutions via mutation, namely using a random mutation rate drawn from a heavy-tailed distribution ("fast mutation", Doerr et al. (2017)) and increasing the mutation strength based on stagnation detection (Rajabi and Witt (2020)). Whereas the latter can obtain the asymptotically best probability of finding a single desired solution in a given distance, the former is more robust and performs much better when many improving solutions in some distance exist. In this work, we propose a mutation strategy that combines ideas of both mechanisms. We show that it can also obtain the best possible probability of finding a single distant solution. However, when several improving solutions exist, it can outperform both the stagnation-detection approach and fast mutation. The new operator is more than an interleaving of the two previous mechanisms and it also outperforms any such interleaving.
