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Suppose a salesperson is planning a sales trip that includes n cities. Each city is connected to some of the other cities by a road. To minimize travel time, the salesperson wants to determine the shortest route that starts at the salesperson’s home city, visits each of the cities once, and ends up at the home city. This problem of finding the shortest route is called the Travelling Salesperson Problem (TSP) and is a well-known problem that can be solved using Dynamic Programming. Research about the TSP problem and find an algorithm based on Dynamic Programming for that. Explain the approach, the algorithm, and its time complexity. Use an example to explain the way the algorithm operates

Subject : Algorithm and Data Structure

Question 2 a) Given the following undirected graph: LO 5 1 3 LO 5 Represent the graph as: (i) Adjacency matrix (ii) Adjacency list (iii) Incidence matrix 4 2 6 15 20 2 4 10 7 3 3 2

Prim's MST approach may be used with a real weighted network.

Dynamic ProgrammingConsider the following network below:   (a) Label all of the nodes such that for every arc, (i,j), where i is the start and j the end node for the arc, the labels satisfy i < j.(b) Why can we use the node labeling algorithm to label the nodes in this network? (c) Use forward DP to find the shortest path from your first labeled node to every node in the network.(d) What fundamental characteristic of dynamic programs allow us to breakdown large-sized problems into a series of smaller-sized problems? What does this characteristic establishes?

PLEASE answer ASAP I will give upvotes if you answer as soon as possible This is Iterative Improvement

a) Given the following undirected graph: 4 1 5 3 Represent the graph as: (i) Adjacency matrix (ii) Adjacency list (iii) Incidence matrix 5 9 A 6 15 20 2 10 7 3 درا 2

5. For the graph below: 7 5 9 20 3. 1 1 1 3 (Route length is the sum of the weights of the edges in the route. When no weight is assigned to an edge the weight is assumed to be 1.) What is the shortest route from 5 to 5 to 2?

The following graph shows the distances, in units of 100 km, between 12 cities. B 3 D 3 7 3 5 E 4 F 3 G 3 H 6 3 5 J 3 K 1 L (i) (ii) Find two different spanning trees. Determine the minimal spanning tree. 2.