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Describe the trees produced by breadth-first search anddepth-first search of the complete bipartite graph \({{\bf{K}}_{{\bf{m,n}}}}\), starting at a vertex of degree m, where m and n are positive integers. Justify your answers.

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01

method for finding breadth first search and depth first search.

In breadth first search first choose a root. Add all edges incident to the root. Then each of the vertices at level 1, add all edges incident with ta vertex not included in the tree yet. And repeat until all vertices were added to the tree.

And

In depth first search starts from any random chosen root and then create a path by successively adding vertices to the path that we adjacent to the previous vertex in the path and the vertex that is added cannot be in the path.

02

Use breadth first search method.

Consider a complete bipartite graph \({{\bf{K}}_{{\bf{m,n}}}}\) with vertex set \({\bf{(}}{{\bf{u}}_{\bf{1}}}{\bf{,}}{{\bf{u}}_{\bf{2}}}{\bf{,}}....{{\bf{u}}_{\bf{m}}}{\bf{)}}\) and \({\bf{(}}{{\bf{v}}_{\bf{1}}}{\bf{,}}{{\bf{v}}_{\bf{2}}}{\bf{,}}....{{\bf{v}}_{\bf{n}}}{\bf{)}}\).Using breadth first search algorithm and choosing vertices alphabetically ,if we start at \({{\bf{v}}_{\bf{1}}}\) as the root of the spanning tree then at level 1 there will be all the vertices of the half of the bipartition \({\bf{(}}{{\bf{u}}_{\bf{1}}}{\bf{,}}{{\bf{u}}_{\bf{2}}}{\bf{,}}....{{\bf{u}}_{\bf{m}}}{\bf{)}}\) ,because they are the only neighbors \({{\bf{v}}_{\bf{1}}}\) of who are no so pairwise among themselves. Choose and all the remaining vertices of the other bipartition are neighbors of \({{\bf{u}}_{\bf{1}}}\) any edges between \({{\bf{v}}_{\bf{i}}}{\bf{,}}{{\bf{v}}_{\bf{j}}}\) .

Hence, they are the children of at level 2 as well as the leaves of the tree.

03

Use depth first search method.

Using depth first search algorithm, the spanning tree of \({{\bf{K}}_{{\bf{m,n}}}}\) starts at the root and then the next child \({{\bf{u}}_{\bf{1}}}\) is, who has a child in \({{\bf{v}}_{\bf{2}}}\) which in turn has only child \({{\bf{u}}_{\bf{2}}}\) and so on. This process continues until either of the bipartition is exhausted. If \({\bf{m = n}}\), the only leaf will be \({{\bf{u}}_{\bf{m}}}\). For the case \({\bf{n < m}}\), the leaves of the trees as well as the children of \({{\bf{v}}_{\bf{n}}}\) will be \({\bf{(}}{{\bf{u}}_{\bf{1}}}{\bf{,}}{{\bf{u}}_{\bf{2}}}{\bf{,}}....{{\bf{u}}_{\bf{m}}}{\bf{)}}\) and the case \({\bf{n > m}}\) can be as likewise figured.

Therefore, this is the required result.

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Most popular questions from this chapter

In Exercises 2โ€“6 find a spanning tree for the graph shown byremoving edges in simple circuits.

a) Define a full \(m{\bf{ - }}\)ary tree.

b) How many vertices does a full \(m{\bf{ - }}\)ary tree have if it has \({\bf{i}}\) internal vertices\(?\) How many leaves does the tree have?

Using alphabetical order, construct a binary search treefor the words in the sentence โ€œThe quick brown fox jumpsover the lazy dog.โ€

Sollin's algorithm produces a minimum spanning tree from a connected weighted simple graph \({\bf{G = (V,E)}}\) by successively adding groups of edges. Suppose that the vertices in \({\bf{V}}\) are ordered. This produces an ordering of the edges where \({\bf{\{ }}{{\bf{u}}_{\bf{0}}}{\bf{,}}{{\bf{v}}_{\bf{0}}}{\bf{\} }}\) precedes \({\bf{\{ }}{{\bf{u}}_{\bf{1}}}{\bf{,}}{{\bf{v}}_{\bf{1}}}{\bf{\} }}\) if \({{\bf{u}}_{\bf{0}}}\) precedes \({{\bf{u}}_{\bf{1}}}\) or if \({{\bf{u}}_{\bf{0}}}{\bf{ = }}{{\bf{u}}_{\bf{1}}}\) and \({{\bf{v}}_{\bf{0}}}\) precedes \({{\bf{v}}_{\bf{1}}}\). The algorithm begins by simultaneously choosing the edge of least weight incident to each vertex. The first edge in the ordering is taken in the case of ties. This produces a graph with no simple circuits, that is, a forest of trees (Exercise \({\bf{24}}\) asks for a proof of this fact). Next, simultaneously choose for each tree in the forest the shortest edge between a vertex in this tree and a vertex in a different tree. Again the first edge in the ordering is chosen in the case of ties. (This produces a graph with no simple circuits containing fewer trees than were present before this step; see Exercise \({\bf{24}}\).) Continue the process of simultaneously adding edges connecting trees until \({\bf{n - 1}}\) edges have been chosen. At this stage a minimum spanning tree has been constructed.

Show that the addition of edges at each stage of Sollinโ€™s algorithm produces a forest.

a) How many edges does a tree with \({\bf{n}}\) vertices have?

b) What do you need to know to determine the number of edges in a forest with \({\bf{n}}\) vertices?

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