Q. Suppose you have to travel Iqra University Gulshan campus 1 to Iqra University Main Campus. If the goal is IU Main campus, we need to know the shortest path distances to IU Main Campus. Implement the given Graph using suitable algorithm to find the good solution. 3 Km 4 Km 6 Km Expo Centre Bus National Stadium Stop 6 Km 1 Km 6 Km 12 Km Sir Syed Stop Urdu University Jail Chawrangi 3 Km Igra University Gu Ishan 3 Km 2 Km 7 Km 8 Km 15 Km Iqra Allama Shabbir Rashid Minhas University Patel Hospi tal Shahrah-e-Faisal Ahmed Road Road Main Campus 1 Campus 9 Km 5 Km 7 Km Waterpump Teen Hatti

Q. Suppose you have to travel Iqra University Gulshan campus 1 to Iqra University Main Campus. If the goal is IU Main campus, we need to know the shortest path distances to IU Main Campus. Implement the given Graph using suitable algorithm to find the good solution. 3 Km 4 Km 6 Km Expo Centre Bus National Stadium Stop 6 Km 1 Km 6 Km 12 Km Sir Syed Stop Urdu University Jail Chawrangi 3 Km Igra University Gu Ishan 3 Km 2 Km 7 Km 8 Km 15 Km Iqra Allama Shabbir Rashid Minhas University Patel Hospi tal Shahrah-e-Faisal Ahmed Road Road Main Campus 1 Campus 9 Km 5 Km 7 Km Waterpump Teen Hatti

Database System Concepts

7th Edition

ISBN:9780078022159

Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Chapter1: Introduction

Section: Chapter Questions

Problem 1PE

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Suppose you have to travel Iqra University Gulshan campus 1 to Iqra University Main Campus. If the goal is IU Main campus, we need to know the shortest path distances to IU Main Campus. Implement the given Graph using suitable algorithm to find the good solution. The code should be in Java
Daniel and Ria are taking a road trip from Somerville to Vancouver (that’s in Canada). Because it’s a 52-hour drive, Daniel and Ria decide to switch off driving at each rest stop they visit; however, because Ria has a better sense of direction than Daniel, she should be driving both when they depart and when they arrive (to navigate the city streets). Given a route map represented as a weighted undirected graph G = (V, E, w) with positive edge weights, where vertices represent rest stops and edges represent routes between rest stops, devise an efficient algorithm to find a route (if possible) of minimum distance between Somerville and Vancouver such that Daniel and Ria alternate edges and Ria drives the first and last edge. Specify the space and time complexity.
A tourist representative problem has the following questions: “Given a list of cities and the distances between each pair countries. What is the shortest possible route that visits each country exactly once and returns to the origin country? What is the possible route if the Greedy Algorithm is used? The table below lists down the distances (kilometers) between countries having direct routes as well as the corresponding distances between them. Show your graph and solutions. Manila Hongkong Sydney London New York Los Angeles California Manila - 1116 6260 10760 11740 13700 Hongkong 1116 - 7400 9646 12960 11656 Sydney 6260 7400 - 17020 16020 12078 London 10760 9646 17020 - 5585 8760 New York 11740 12960 16020 5585 - 3944 Los Angeles California 13700 11656 12078 8760 3944 -
A weighted graph is given below. Compute the following metrics for this graph. You can use a calculator if necessary. 1) Eccentricity for each vertex; 2) Average length of the shortest paths from each vertex; 3) Count of triangles of each vertex; 4) Count of triples of each vertex; 5) Radius of the graph; 6) Diameter of the graph; 7) Average path length of the graph; 8) Characteristic path length of the graph; 9) Network transitivity of the graph; 10) Network density of the graph.
Find the shortest path in the graph using the Dijkstra shortest path algorithm?? Please help explain clearly
Let A, B, C, D be the vertices of a square with side length 100. If we want to create a minimum-weight spanning tree to connect these four vertices, clearly this spanning tree would have total weight 300 (e.g. we can connect AB, BC, and CD). But what if we are able to add extra vertices inside the square, and use these additional vertices in constructing our spanning tree? Would the minimum-weight spanning tree have total weight less than 300? And if so, where should these additional vertices be placed to minimize the total weight? Let G be a graph with the vertices A, B, C, D, and possibly one or more additional vertices that can be placed anywhere you want on the (two-dimensional) plane containing the four vertices of the square. Determine the smallest total weight for the minimum-weight spanning tree of G. Round your answer to the nearest integer. Note: I encourage you to add n additional points (for n=1, 2, 3) to your graph and see if you can figure out where these point(s) need to…
Let A, B, C, D be the vertices of a square with side length 100. If we want to create a minimum-weight spanning tree to connect these four vertices, clearly this spanning tree would have total weight 300 (e.g. we can connect AB, BC, and CD). But what if we are able to add extra vertices inside the square, and use these additional vertices in constructing our spanning tree? Would the minimum-weight spanning tree have total weight less than 300? And if so, where should these additional vertices be placed to minimize the total weight? Let G be a graph with the vertices A, B, C, D, and possibly one or more additional vertices that can be placed anywhere you want on the (two-dimensional) plane containing the four vertices of the square. Determine the smallest total weight for the minimum-weight spanning tree of G. Round your answer to the nearest integer. Attention: Please don't just copy these two following answers, which are not correct at all. Thank you.…
Suppose we want to use UCS and the A* algorithm on the graph below to find the shortest path from node S to node G. Each node is labeled by a capital letter and the value of a heuristic function. Each edge is labeled by the cost to traverse that edge. Perform A*, UCS, and BFS on this graph. Indicate the f, g, and h values of each node for the A*. e.g., S = 0 + 6 = 6 (i.e. S = g(S) + h(S) = f(S)). Additionally, show how the priority queue changes with time. Show the order in which the nodes are visited for BFS and UCS. Show the path found by the A*, UCS, and BFS algorithms on the graph above. Make this example inadmissible by changing the heuristic value at one of the nodes. What node do you choose and what heuristic value do you assign? What would be the A* algorithm solution then.
Consider the following network: a.) Find the shortest path from node 1 to node 8 using Dijkstra’s algorithm. Write the length of the shortest path as well as the edges that compose it. b.) Write an integer programming formulation to find the second-shortest path from 1 to 8 in this network. (Hint: if the shortest path is not available, the second-shortest path becomes the shortest path.)
Suppose there is undirected graph F with nonnegative edge weights we ≥ 0. You have also calculated the minimum spanning tree of F and also the shortest paths to all nodes from a particular node p ∈ V . Now, suppose that each edge weight is increased by 1, so the new weights are we′ = we + 1. (a) Will there be a change of the minimum spanning tree? Provide an example where it does or prove that it cannot change. (b) (3 points) Will the shortest paths from p change? Provide an example where it does or prove that it cannot change.
Run the 2-approximation algorithm for the Traveling Salesman problem on the following graph. First, specify a minimal spanning tree in the graph. Then make it clear at which node you start the tour and in which order the edges are considered and skipped if necessary. Then give the cost of the computed tour. Also determine the optimal tour cost and state the factor by which the tour found by the approximation algorithm is more expensive.
(Generic shortest-paths algorithm) Proposition Q Initialise all distTo[] values to infinity and distTo[s] to 0, then carry out the following:Every edge in G should be relaxed until none are left.The value of distTo[w] after this calculation is the length of the shortest path from s to w (and the value of edgeTo[] is the final edge on that path) for all vertices w accessible from s.