论文标题
在参数适应方法中分析适应性参数景观的差异进化方法
Analyzing Adaptive Parameter Landscapes in Parameter Adaptation Methods for Differential Evolution
论文作者
论文摘要
由于规模因子和交叉率显着影响差异演化（DE）的性能，因此在DE社区中已经很好地研究了这两个参数的参数适应方法（PAMS）。尽管PAM可以充分提高DE的有效性，但PAM的理解很少（例如，PAM的工作原理）。理解PAM的困难之一来自由比例因子和交叉速率组成的参数空间的不差异。本文通过分析DE的PAM中的自适应参数景观来解决此问题。首先，我们提出了一个自适应参数景观的概念，该景观捕获了参数适应过程中的一刻。对于每种迭代，人口中的每个人都有其自适应参数景观。其次，我们提出了一种使用1步观察贪婪改进度量的方法来分析自适应参数景观的方法。第三，我们使用所提出的方法检查了PAM中PAM中的自适应参数景观。结果提供了DE中有关PAM的洞察力信息。
Since the scale factor and the crossover rate significantly influence the performance of differential evolution (DE), parameter adaptation methods (PAMs) for the two parameters have been well studied in the DE community. Although PAMs can sufficiently improve the effectiveness of DE, PAMs are poorly understood (e.g., the working principle of PAMs). One of the difficulties in understanding PAMs comes from the unclarity of the parameter space that consists of the scale factor and the crossover rate. This paper addresses this issue by analyzing adaptive parameter landscapes in PAMs for DE. First, we propose a concept of an adaptive parameter landscape, which captures a moment in a parameter adaptation process. For each iteration, each individual in the population has its adaptive parameter landscape. Second, we propose a method of analyzing adaptive parameter landscapes using a 1-step-lookahead greedy improvement metric. Third, we examine adaptive parameter landscapes in PAMs by using the proposed method. Results provide insightful information about PAMs in DE.
