a) Draw the connected subgraph of the given graph above which contains only four nodes ACGB and is also a minimum spanning tree with these four nodes. What is its weighted sum? Draw the adjacency matrix representation of this subgraph (use boolean matrix with only 0 or 1, to show its adjacency in this case).

Consider an undirected graph G with 100 nodes. The maximum number of edges to be included in G so that the graph is not connected is

Please written by computer source

Given the following graph, A C 3 1 E 4 В F 7 D 5 What is the next edge and vertex(s) to be included in the solution if a. we are using Prim's algorithm to find a minimum spanning tree and we have started with vertex E? Edge: Vertex(s): What is the next edge and vertex(s) to be included in the solution if b. we are using Kruskal's algorithm to find a minimum spanning tree Edge: Vertex(s): What is the next edge and vertex(s) to be included in the solution if c. we are using Dijkstra's shortest path algorithm to find shortest paths and we have started with vertex E, with C and F already included in the shortest path tree? Edge: Vertex(s):

Given N cities represented as vertices V₁, V2,..., UN on an undirected graph (i.e., each edge can be traversed in both directions). The graph is fully-connected where the edge eij connecting any two vertices v; and vj is the straight-line distance between these two cities. We want to search for the shortest path from v₁ (the source) to VN (the destination). Assume that all edges have different values, and e₁, has the largest value among the edges. That is, the source and destination have the largest straight-line distance. Compare the lists of explored vertices when we run the uniform-cost search and the A* search for this problem. Hint: The straight-line distance is the shortest path between any two cities. If you do not know how to start, try to run the algorithms by hand on some small cases first; but remember to make sure your graphs satisfy the conditions in the question.

Let G = (V, E) be an undirected graph and each edge e ∈ E is associated with a positive weight ℓ(e).For simplicity we assume weights are distinct. Is the following statement true or false? Let T be a minimum spanning tree for the graph with the original weight. Suppose we replace eachedge weight ℓ(e) with ℓ(e)^2, then T is still a minimum spanning tree.

You are given a weighted tree T.(As a reminder, a tree T is a graph that is connected and contains no cycle.) Each node of the tree T has a weight, denoted by w(v). You want to select a subset of tree nodes, such that weight of the selected nodes is maximized, and if a node is selected, then none of its neighbors are selected.

Write to code describes how to create the links dataset that represents the input graph. In this particular case, the links represent a directed network. The links dataset has only the nodes identification, which means, the from and to variables. The link weights in the transitive closure problem are irrelevant. In other words, it doesn’t matter the cost or the weight of the links, the algorithm searches for the possible paths to connect the nodes within the input graph. If there is a link or a set of links, no matter the weights, that connects node i to node j, that is the matter.

Question 1: In graph theory, a graph X is a "complement" of a graph F if which of the following is true?   Select one:   a. If X is isomorph to F, then X is a complement of F.   b. If X has half of the vertices of F (or if F has half of the vertices of X) then X is a complement of F.   c. If X has the same vertex set as F, and as its edges ONLY all possible edges NOT contained in F, then X is a complement of F.   d. If X is NOT isomorph to F, then X is a complement of F.   Question 2: Which statement is NOT true about Merge Sort Algorithm:   Select one:   a. Merge Sort time complexity for worst case scenarios is: O(n log n)   b. Merge Sort is a quadratic sorting algorithm   c. Merge Sort key disadvantage is space overhead as compared to Bubble Sort, Selection Sort and Insertion Sort.   d. Merge Sort adopts recursive approach

We recollect that Kruskal's Algorithm is used to find the minimum spanning tree in a weighted graph. Given a weighted undirected graph G = (V , E, W), with n vertices/nodes, the algorithm will first sort the edges in E according to their weights. It will then select (n-1) edges with smallest weights that do not form a cycle. (A cycle in a graph is a path along the edges of a graph that starts at a node and ends at the same node after visiting at least one other node and not traversing any of the edges more than once.) Use Kruskal's Algorithm to nd the weight of the minimum spanning tree for the following graph.