EDO Data

Despite their various uses, the uptake of evolutionary algorithms in industry remains limited. In order to understand why uptake is low a survey of engineers was undertaken, the results of which are presented here. A total of 23 participants (N = 23) took part in the 3-part mixed methods survey. Reflexive thematic analysis was conducted on the open-ended questions. A common thread throughout participants responses is that there is a question of trust towards evolutionary algorithms within industry. Perhaps surprising is that the key to gaining this trust is not producing good results, but creating algorithms which explain the process they take in reaching a result. Based on this, recommendations have been made to increase their use in industry.

尽管进化算法（evolutionary algorithms）拥有诸多应用场景，但其在工业界的采用率仍较为有限。为探明其采用率偏低的原因，本研究开展了一项面向工程师的调研，相关调研结果即呈现于此。本次调研分为三个部分，采用混合研究方法，共计有23名受访者参与（N=23）。针对调研中的开放式问题，研究采用了反思性主题分析方法。受访者的回复中贯穿一条核心线索：工业界对进化算法存在信任疑虑。值得注意的是，获取此类信任的关键并非仅在于产出优质结果，而是研发能够解释自身得出结果的完整过程的进化算法。基于上述发现，本研究提出了相关建议，以提升进化算法在工业界的应用普及率。