TITLE: Problems and Algorithms Requiring Non-Bipartite Matching
QUESTION [5 upvotes]: While the importance of the non-bipartite matching problem itself from an algorithmic and complexity point of view is well known, applications of non-bipartite matching are hard to find.
I did an online search for hints, but almost always the articles I found lacked problems that demonstrated the need for non-bipartite matching. The few exceptions I found were:  

A scheduling problem [Fujii, Kasami & Ninomiya, 1969] described in Gerard's matching survey 
The oil well drilling problem of [Devine 1973] described in Gerard's matching survey 
The Christofides heuristic for the TSP [Christofides 1976] Wikipedia 
Plotting street maps with minimum pen lifting [Iri&Taguchi 1980] described in Gerard's matching survey 
Kekule structures in chemistry described here 
Nonparametric Tests for Homogeneity [Rosenbaum 2005] described here 
TSP: unraveling of tours with a high number of pairs of crossing edges: 
Generate a graph $\Gamma$ in which the edges correspond to pairs of crossing tour edges and their weight equals the amount by which the tour length decreases when replacing the respective tour edges by a pair of non-crossing ones.
The maximum weight matching in $\Gamma$ identifies the pairs of tour-edges whose exchanging incurs the maximal length reduction.
That matching may have to be applied several times until all crossings have been removed.  
Optimizing Triangulations: take as nodes the triangles and as edges the sides that are shared by two triangles; in that settig a plethora of cost functions can be envisaged for different optimality criteria.
There are two basic operations that can be performed on triangulations, namely 

diagonal-swapping for the purpose of improving a triangulation:   


minimum weight matching with length reduction incurred by swapping diagonals as edge cost when striving for minimum weight triangulations
maximum weight matching with the increment of the geometric angle between edge-adjacent triangles when striving for "smooth" triangulations like e.g. of terrain data  
maximum weight matching with the most acute geometric angle of a triangle as edge cost when striving for triangulations of e.g. terrain data, that are in the spirit of planar Delaunay triangulations.

merging edge-adjacent triangles for the purpose of generating a quadrilateralization:


a minimum weight matching with the circumference of the generated quadrilateral as edge-cost when striving for "fine grained" quadrilateralizations
a maximum weight matching over the most acute geometric angle of a generated quadrilateral when striving for the most orthogonal  quadrilateralization e.g. for use as finite elements or, as patches for spline interpolation of 3D data.
a minimum weight matching with the spatial distance between a quadrilateral's diagonals when striving for quadrilateralizations with planar cells.   



Question
are there further applications for non-bipartite matching, especially newer, examples of different areas of applicability?

REPLY [2 votes]: See "Optimal Nonbipartite Matching and Its Statistical Applications" by Lu et al. in The American Statistician Feb 2011.