Minimum sum of squared Euclidean distance between two arrays

Question

Question:
Given two sorted sequences in increasing order, $X$ and $Y$. $Y$ is of size $k$ and $X$ is of size $m$.
I would like to find a subset of $X$, $i.e$, $X'$ of size $k$, and considering the following optimization problem:$$d(Y,X') = \sum_{j=1}^{k}(y_{j}-x'_{j})^{2}$$ And $X'$ is a subset of $X$ of size $k$, $y_{j} \text{ and } x'_{j}$ is element in $Y$ and $X'$. I would like to find the subset of $X$, to reach the minimum of $d(Y,X')$.
Note that $X'$ could have $k!$ numbers of arrangements, so its order is totally unknown.

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What I have came up with so far:
I would like to approach it using Dynamic Programming, and I think I would first compute the squared distance between each element in $Y$ and $X$, but I'm having trouble in determining what is the subproblem and how to solve ths using DP. Thank you!

Update: The $X'$ could be sorted, which means we could aim at finding a sorted subset of $X$.

Answer 1

for m' = 0 to m for k' = max(0, m-m') to min(m', k) Take the problem of the first m' items of X and the first k' items of Y. Find the value of the smallest sum, and whether X[m'] is in that sum.

The optimal subset of the first m' items of X is either the best subset of the first m'-1 items of X matching the first k' items of Y, or the best subset of the first m'-1 items of X matching the first k'-1 items of Y, with X[m'] and Y[k'] added.

Note that sets and subsets are not sorted. If you want the indexes in arbitrary order, sorting X and Y first should work.