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Instructions Implement a single source shortest path algorithm for a given graph structure. You can use any of the listed algorithms that you have read thus far. You do not have to write them yourself, you may take them from some source, but you must reference your source. Utilize one of the examples listed below: $ 5 14 5 6 10 20 4 30 5 20 15 2 3 6 10 5 15 1 10 10 25 11 9 7 5 3 - (11 5 20 (2) 15 5 2 17 8 15 8 15 5 20 10 € - 9 10 12 * (10) Figure 4 2 I 2 8 4 A B c I 3/ 10 2 10 3 , , 4 5 D 9 E F 2 G x 4 3 1 . 7 H I 8 A B c 2 10 5 D 9 E (F) 4 2 G H I You are to submit a paper written with Microsoft Word that discusses the results of your analysis. It should include the following: A brief introduction of the algorithm(s) that you have selected and how the algorithm(s) compare, if any A discussion of the critical operation that you chose to count with an explanation of why you selected it A Big-O analysis of the algorithm(s) used. Make sure that critical operation count is included with this discussion. Comprehensive Test Plan with Step-by-step instructions, limitations, and expectation of results for user o Comprehensive Documentation containing Approach, Lessons Learned, and Possible Improvements sub-sections o A conclusion that summarizes the important observations of your study

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Brief Introduction of the Used Algorithm

The algorithm used for finding the single source shortest path in this project is based on Bellman-Ford’s approach. Among the most-known applications can be highlighted the RIP (Routing Information Protocol) and network flow analysis (for cycle cancellation).
The present algorithm is used to discover the shortest paths from a single source node to the other vertices. A strong point is represented by the fact that it is usable in a weighted directed graph; although it performs slower than classical Dijkstra’s algorithm it is applicable in a wider range of situations because it can handle graphs where some of the edge weights are negative numbers.
The “relaxation” is applied by |V|-1 times to all edges (V is the number of nodes of the initial graph). At each step the number of nodes (having the distance correctly calculated) grows and in the end all vertices have their correct distances assigned....

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