Download PDF by Hiroshi Nagamochi: Algorithmic aspects of graph connectivity

By Hiroshi Nagamochi

ISBN-10: 0521878640

ISBN-13: 9780521878647

Algorithmic elements of Graph Connectivity is the 1st entire ebook in this relevant suggestion in graph and community idea, emphasizing its algorithmic facets. as a result of its huge purposes within the fields of verbal exchange, transportation, and construction, graph connectivity has made large algorithmic growth less than the effect of the idea of complexity and algorithms in glossy laptop technological know-how. The e-book comprises a variety of definitions of connectivity, together with edge-connectivity and vertex-connectivity, and their ramifications, in addition to similar issues comparable to flows and cuts. The authors comprehensively talk about new strategies and algorithms that let for faster and extra effective computing, corresponding to greatest adjacency ordering of vertices. overlaying either simple definitions and complex themes, this booklet can be utilized as a textbook in graduate classes in mathematical sciences, akin to discrete arithmetic, combinatorics, and operations study, and as a reference booklet for experts in discrete arithmetic and its functions.

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10 ([72]). If all edge weights in an edge-weighted digraph G = (V, E) are integers, then there exists a maximum (s, t)-flow f such that f (e) is an integer for every edge e ∈ E, and there is an algorithm to compute such f in finite computation time. 10 is not efficient for digraphs with large edge weights and may not terminate in finite iterations if the digraph G has edges whose weights are irrational numbers [73]. Edmonds and Karp [61] first gave a maximum flow algorithm that runs in time polynomial in n and m.

Karzanov [183] and Even and Tarjan [66] have shown the following properties, based on which the time complexity of Dinits’ algorithm will be further elaborated. 12 ([66, 183]). Let G = (V, E) be an unweighted digraph, and s, t ∈ V be given. Then (i) λ(s, t; G)· dist(s, t; G) ≤ m. (ii) If G has no multiple edges, then λ(s, t; G)· dist(s, t; G) ≤ n. (iii) If G has no multiple edges and |E(v, V − v; G)| ≤ 1 or |E(V − v, v; G)| ≤ 1 holds for every v ∈ V − {s, t}, then λ(s, t; G) · ( dist(s, t; G) −1) ≤ n − 2.

I) By letting cG (e) = 1 for all edges e in the digraph G = (V, E), we consider an integer-valued maximum (s, t)-flow f and a minimum (s, t)-cut X . 10, v( f ) = d(X ; G) holds, where v( f ) denotes the flow value of f . 1, we can decompose f into a set of weighted (s, t)-paths and weighted directed cycles such that the sum of weights of the paths is v( f ). Since f is integer-valued and cG (e) = 1 for all edges e, the set of weighted paths consists of v( f ) edge-disjoint (s, t)-paths, as required.

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Algorithmic aspects of graph connectivity by Hiroshi Nagamochi

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