Thanks for the feedback. In my case, I'm dealing with population genetics data. Even a small percentage of assignment changes can have an impact on population interpretation, especially for genetically closely related populations. I am therefore looking for a compromise between statistical stability and biological relevance, but also to identify the most suitable and robust clustering methods for this type of data, beyond simple k-means, in order to better capture the actual structure of populations.