Introduction to Algorithms
3rd Edition
ISBN: 9780262033848
Author: Thomas H. Cormen, Ronald L. Rivest, Charles E. Leiserson, Clifford Stein
Publisher: MIT Press
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Chapter 33.1, Problem 8E
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To show the process of computing the area of an n vertex simple but not necessarily convex, polygon in time.
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Describe a linear-time algorithm for computing the strongconnected component containing a given vertex v. On the basis of that algorithm, describe a simple quadratic algorithm for computing the strong components of a digraph.
Describe a linear-time algorithm for computing the strongn connected component containing a given vertex v. On the basis of that algorithm, describe a simple quadratic algorithm for computing the strong components of a digraph.
Describe a linear-time algorithm for computing the strong connected component containing a given vertex v. On the basis of that algorithm, describe a simple quadratic algorithm for computing the strong components of a digraph.
Chapter 33 Solutions
Introduction to Algorithms
Ch. 33.1 - Prob. 1ECh. 33.1 - Prob. 2ECh. 33.1 - Prob. 3ECh. 33.1 - Prob. 4ECh. 33.1 - Prob. 5ECh. 33.1 - Prob. 6ECh. 33.1 - Prob. 7ECh. 33.1 - Prob. 8ECh. 33.2 - Prob. 1ECh. 33.2 - Prob. 2E
Ch. 33.2 - Prob. 3ECh. 33.2 - Prob. 4ECh. 33.2 - Prob. 5ECh. 33.2 - Prob. 6ECh. 33.2 - Prob. 7ECh. 33.2 - Prob. 8ECh. 33.2 - Prob. 9ECh. 33.3 - Prob. 1ECh. 33.3 - Prob. 2ECh. 33.3 - Prob. 3ECh. 33.3 - Prob. 4ECh. 33.3 - Prob. 5ECh. 33.3 - Prob. 6ECh. 33.4 - Prob. 1ECh. 33.4 - Prob. 2ECh. 33.4 - Prob. 3ECh. 33.4 - Prob. 4ECh. 33.4 - Prob. 5ECh. 33.4 - Prob. 6ECh. 33 - Prob. 1PCh. 33 - Prob. 2PCh. 33 - Prob. 3PCh. 33 - Prob. 4PCh. 33 - Prob. 5P
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- What is the worst case time complexity of an adjacency maatrix for printing the vertex of all the neighbors of a vertex? Choose one: O(V) O(E) O(1) O(V+E)arrow_forwardDevelop a version of Dijkstra’s algorithm that can find the SPT from a given vertex in a dense edge-weighted digraph in time proportional to V2. Use any adjacency-matrix representationarrow_forwardLet A and B each be sets of N labeled vertices, and consider bipartite graphs between A and B. What is the maximum number of edges possible for any bipartite graph between A and B?arrow_forward
- Prove by induction that a graph with n vertices has at most n(n-1)/2arrow_forwardDesign an algorithm to find the shortest (directed) cycle containing a vertex v. What is the space and time complexity of your algorithm? Prove that your algorithm finds the shortest cycle.arrow_forwardRecall from lecture that an m × n grid graph has m rows of n vertices, where vertices next to each other are linked by an edge. Find the greatest length of any path in such a graph, and provide a brief explanation as to why it is maximum. You may assume m, n ≥ 2.arrow_forward
- 4. Determine the Prufer code of a path of length n, when vertex i is a neighbour of vertex i − 1 and i + 1, for i = {2, · · · , n − 1}.arrow_forwardRun experiments to determine empirically the average number ofvertices that are reachable from a randomly chosen vertex, for various digraph modelsarrow_forward3. From the graph above determine the vertex sequence of the shortest path connecting the following pairs of vertex and give each length: a. V & W b. U & Y c. U & X d. S & V e. S & Z 4. For each pair of vertex in no. 3 give the vertex sequence of the longest path connecting them that repeat no edges. Is there a longest path connecting them?arrow_forward
- Let H be a planar graph with n vertices and m edges, where n >= 5. Prove that if H does not have any cycles of length 3 and 4 then 3m <= 5n - 10.arrow_forwardLet G be a DAG with n vertices. How many strongly connected components are therein G? Show your completed work and justify your answer.arrow_forwardProve by contradiction that BFS computes the shortest path starting from a given source vertex s. Feel free to introduce suitable notation for the proof.arrow_forward
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