Примеры использования Augmenting path на Английском языке и их переводы на Русский язык
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A network is at maximum flow if andonly if there is no augmenting path in the residual network Gf.
An augmenting path is an s- t{\displaystyle s-t}path  in the residual graph G f{\displaystyle G_{f.
However, for non-bipartite graphs, the task of finding the augmenting paths within each phase is more difficult.
One can prove that a matching is maximum if andonly if it does not have any augmenting path.
Notice how the length of the augmenting path found by the algorithm(in red) never decreases.
The matching is constructed by iteratively improving an initial empty matching along augmenting paths in the graph.
Finally, it locates an augmenting path P′ in the contracted graph(line B22) and lifts it to the original graph line B23.
The algorithm finds a maximal set of vertex disjoint augmenting  paths of length k{\displaystyle k.
If no augmenting path can be found, an algorithm may safely terminate, since in this case M{\displaystyle M} must be optimal.
That is, a vertex v{\displaystyle v} is put into F{\displaystyle F} if andonly if it ends a shortest augmenting path.
Once an augmenting path is found that involves one of the vertices in F{\displaystyle F}, the DFS is continued from the next starting vertex.
Let us now prove the contrapositive of Berge's lemma: G has a matching larger than M if andonly if G has an augmenting path.
However, instead of finding just a single augmenting path per iteration, the algorithm finds a maximal set of shortest augmenting paths. .
Thus, whenever there exists a matching M∗{\displaystyle M^{*}}larger than the current matching M{\displaystyle M}, there must also exist an augmenting path.
By Berge's lemma, matching M is maximum if andonly if there is no M-augmenting path in G. Hence, either a matching is maximum, or it can be augmented. .
Since M′ is larger than M,D contains a component that has more edges from M′ than M. Such a component is a path in G that starts and ends with an edge from M′, so it is an augmenting path. .
Note that the number of unmatched edges in an augmenting path is greater by one than the number of matched edges, and hence the total number of edges in an augmenting path is odd.
But then one of M and M′ must have one fewer edge than the other in this component,meaning that the component as a whole is an augmenting path with respect to that matching.
In each iteration the algorithm either(1) finds an augmenting path,(2) finds a blossom and recurses onto the corresponding contracted graph, or(3) concludes there are no augmenting paths. .
Therefore, once the initial| V|{\displaystyle{\sqrt{|V|}}} phases of the algorithm are complete,the shortest remaining augmenting path has at least| V|{\displaystyle{\sqrt{|V|}}} edges in it.
An augmenting path in a matching problem is closely related to the augmenting paths  arising in maximum flow problems,paths  along which one may increase the amount of flow between the terminals of the flow.
However, the symmetric difference of the eventual optimal matching and of the partial matching M found by the initial phases forms a collection of vertex-disjoint augmenting paths and alternating cycles.
The basic concept that the algorithm relies on is that of an augmenting path,  a path  that starts at a free vertex, ends at a free vertex, and alternates between unmatched and matched edges within the path.
For instance, in the average case for sparse bipartite random graphs, Bast et al.(2006)(improving a previous result of Motwani 1994)showed that with high probability all non-optimal matchings have augmenting paths of logarithmic length.
It can be shown that each phase increases the length of the shortest augmenting path by at least one: the phase finds a maximal set of augmenting paths of the given length, so any remaining augmenting  path must be longer.
Their results in general tend to show that the Hopcroft-Karp method is not as good in practice as it is in theory: it is outperformed both by simpler breadth-first anddepth-first strategies for finding augmenting paths, and by push-relabel techniques.
If M{\displaystyle M} is a matching, andP{\displaystyle P} is an augmenting path relative to M{\displaystyle M}, then the symmetric difference of the two sets of edges, M⊕ P{\displaystyle M\oplus P}, would form a matching with size| M|+ 1{\displaystyle|M|+1.
Clearly, an augmenting path P of G can be used to produce a matching M′ that is larger than M- just take M′ to be the symmetric difference of P and M M′ contains exactly those edges of G that appear in exactly one of P and M.
Berge's lemma states that a matching M in a graph G is maximum(contains the largest possible number of edges) if andonly if there is no augmenting path(a path  that starts and ends on free(unmatched) vertices, and alternates between edges in and not in the matching) with M. It was proven by French mathematician Claude Berge in 1957 though already observed by Petersen in 1891 and Kőnig in 1931.
This means that we can use augmenting paths p 1{\displaystyle p_{1}}, p 2{\displaystyle p_{2}}, p 1{\displaystyle p_{1}} and p 3{\displaystyle p_{3}} infinitely many times and residual capacities of these edges will always be in the same form.