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Fitness function for finding out robust solutions on time-varying functions

机译:适应度函数,用于寻找时变函数的健壮解决方案

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Evolutionary Computations in dynamic/uncertain environments have attracted much attention. Studies regarding this research subjects can be classified into four categories: Noise, Robustness, Fitness approximation, and Time-Varying function. In research on Time-Varying function, the tracking property over changes of fitness landscape has been broadly and deeply researched so far. In this paper, instead of tracking new peaks, robust solution to Time-Varying functions is introduced. Moreover, two weighted fitness functions, Exponential Weight and Linear Weight, are proposed. Experiments on modified Branke's benchmark problems on Time-Varying function reveal the effectiveness of the weighted approaches.
机译:动态/不确定环境中的进化计算已引起广泛关注。关于该研究主题的研究可以分为四类:噪声,鲁棒性,适应度近似和时变函数。在时变功能的研究中,迄今为止对健身景观变化的跟踪特性已经进行了广泛而深入的研究。在本文中,不是跟踪新的峰值,而是引入了时变函数的鲁棒解决方案。此外,提出了两个加权适应度函数,指数权重和线性权重。修改后的Branke时变函数基准问题的实验证明了加权方法的有效性。

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