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We are given a set of vertices and betweenness constraints.
First, we show that, given a set of vertices with specified weights, one can construct a tree that connects all vertices and enables broadcasting from any vertex in the optimal time of Θ logn).
In this problem, we are given a set of vertices including a central depot, customer and facility vertices where each facility can supply the demand of some customers within its pre-determined coverage distance.
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Second, given a set of weighted vertices among which one vertex is specified as the originator, we introduce a polynomial algorithm that connects vertices with a tree in which broadcasting from the originator completes in minimum time.
Given a set of weighted vertices V and a multiset of integers S, we consider the problem of constructing a tree on V whose splits correspond to S. The problem is known to be NP-complete, even when all vertices have unit weight and the maximum vertex degree of T is required to be at most 4. We show that.
Given a set of grouped vertices, denoted as (X'), we simply add a virtual node (x_v) to the graph to represent (X').
We then discuss a more problem - given a set of configurations on the vertices of a graph (for example colorings), how do we sample from that?
Given a set of proteins, they are represented as different paths over a graph that consists of 20 vertices, corresponding to the 'alphabet' of 20 amino-acids.
Given a set F of vertices of a connected graph G, we study the problem of testing the connectivity of G−F in polynomial time with respect to |F| and the maximum degree Δ of G.
Given a set X of vertices, edges, or arcs in a graph G, let G∖ X denote the graph obtained by deleting X from G. When X has only one element x, we might also write G∖ x instead of G∖{ x}.
Formally, a graph is given by a set of vertices V and a set of edges E. The degree of a node u ∈ V, denoted by d u), is the number of edges adjacent to u.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com