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| courses:cs211:winter2011:journals:charles:chapter6 [2011/03/30 04:29] – [6.8 Shortest Paths in a Graph] gouldc | courses:cs211:winter2011:journals:charles:chapter6 [2011/03/30 04:30] – [6.8 Shortest Paths in a Graph] gouldc | ||
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| We do this by incorporating divide-and-conquer principles into our algorithm. I'm slightly confused by the divide-and-conquer component to this problem. In class we did it with the graph in Figure 6.19. We started in the top left and found the shortest path to some midpoint, then we did the same thing from the bottom right. I will need to look in more depth at the pseudo-code on page 288 to get a better grasp of the concept. | We do this by incorporating divide-and-conquer principles into our algorithm. I'm slightly confused by the divide-and-conquer component to this problem. In class we did it with the graph in Figure 6.19. We started in the top left and found the shortest path to some midpoint, then we did the same thing from the bottom right. I will need to look in more depth at the pseudo-code on page 288 to get a better grasp of the concept. | ||
| ===== 6.8 Shortest Paths in a Graph ===== | ===== 6.8 Shortest Paths in a Graph ===== | ||
| - | This section is about finding the shortest path between two nodes in a directed graph. Each edge has a weight. If there are no negative cycles (cycles that decrease the total cost of the path), then we want to find the path from s -> t that minimizes total edge costs... the shortest path. | + | This section is about finding the shortest path between two nodes in a directed graph. Each edge has a weight. If there are no negative cycles (cycles that decrease the total cost of the path), then we want the path from s -> t that minimizes |
| starting node s and destination node t with minimum total cost. Each edge in the graph has an associated weight. | starting node s and destination node t with minimum total cost. Each edge in the graph has an associated weight. | ||
| This section is about using a memoized array to keep track of the shortest paths in a graph. The new method is contrasted with Dijkstra' | This section is about using a memoized array to keep track of the shortest paths in a graph. The new method is contrasted with Dijkstra' | ||
