Maximum matching versus preferential assignment
After some introspection, I'd like to suggest the following natural problem. A  skew-symmetric digraph is a digraph $G$ where each vertex comes in two copies $v,v'$ (possibly identical) and such that for each arc $(u,v) \in A(G)$ we also have $(v',u') \in A(G)$. The problem consists of packing cycles in a skew-symmetric digraph under a weight constraint. That is to say, we are given a ssd $G = (V,A)$, a weighting $w : V \rightarrow \mathbb{N}$ s.t. $w(v') = w(v)$ for each $v \in V$, and an integer $k$, and we seek a family of $k$ cycles $\cal{C}$ in $D$ such that (i) $V(\cal{C})$ has maximum cardinality, (ii) each $C \in \cal{C}$ is skew-symmetric, i.e. if it contains $(u,v)$ then it also contains $(v',u')$, (iii) each vertex $v$ is contained in at most $w(v)$ cycles of $D$.

This problem would generalize two well-known problems in combinatorial optimizations: (1) maximum matchings in undirected graphs and (2) maximum $k$-chains in posets. Here is a sketch of the reductions. For problem (1) we start with an undirected graph $G$, and we let $D$ be the symmetric digraph obtained from $G$ with each vertex self-symmetric, assigning a weight one to each vertex. For problem (2) we start with a poset $P_0$ with underlying digraph $D_0$, and we let $D$ be the digraph obtained by taking the disjoint union of $D_0$, its symmetric copy, and arcs $(v,v'), (v',v)$ for each vertex $v$ of $P$; we assign a weight one to each vertex.

I'm not sure about the practical application of your problem, but I expect it to be P-hard: a reduction from 3HornSat to the weighted version seems possible although I didn't check the details. If this problem turned out to be in P (with a corresponding min/max result) it would be very interesting, at least from a theoretical standpoint.