Given $n$ points, each point $x_i$ has a value $v_i \in \mathbb{R}^{d}$, and there are $m$ point sets $\{S_1,\dots, S_m\}$ that each point set consists of some points. The size of point sets can be different. Moreover, we define the mean value of each set as
$$v_{s_i} = \frac {1}{|S_i|} \sum_{x_j \in S_i}{v_j}$$
the target is to add or delete $k$ points from the $m$ sets. For example, we add $x_i$ into $S_j$, which is one operation. The target is to conduct $k$ operations to minimize the distance
$$\displaystyle\sum_{i=1}^m{\sum_{j=1}^m{(v_{s_i}-v_{s_j}})^2} \tag{1}$$
or
$$\displaystyle\sum_{j=1}^m{(v_{s_i}-\bar{v}_{s}})^2 \tag{2}$$
where $\bar{v}_{s}=\frac{1}{m} \displaystyle\sum_{j=1}^m{v_{s_j}}$.
I think that minimizing any goal of $(1)$ and $(2)$ is NP-hard, but how to prove it? Are there any approximation algorithms with a constant approximation ratio?