Adaptive differential evolution and exponential crossover

J. Tvrdík
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引用次数: 31

Abstract

Several adaptive variants of differential evolution are described and compared in two sets of benchmark problems. The influence of exponential crossover on efficiency of the search is studied. The use of both types of crossover together makes the algorithms more robust. Such algorithms are convenient for the real-world problems, where we need an adaptive algorithm applicable without time-wasting parameter tuning.
自适应差分进化与指数交叉
描述了差分进化的几种自适应变体,并在两组基准问题中进行了比较。研究了指数交叉对搜索效率的影响。同时使用两种类型的交叉使得算法更加稳健。这样的算法对于现实世界的问题来说是很方便的,在现实世界中,我们需要一种不需要耗费时间的参数调优的自适应算法。
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