Computer Science BS Journal (CST370) : Week 6

 This week in CST370 introduced several advanced algorithm techniques for optimization and graph problems. We began with non-comparison sorting, such as counting sort or radix sort, which sort data without directly comparing elements. These algorithms can achieve linear time under certain conditions, making them faster than traditional comparison-based sorts.

We then studied dynamic programming, a method that solves complex problems by breaking them into overlapping subproblems and storing solutions to avoid repeated work. This approach is powerful for optimization problems like shortest paths or resource allocation.

Next, we covered Warshall’s algorithm, which computes the transitive closure of a graph. It determines which vertices are reachable from others, helping analyze connectivity. Related to this, Floyd’s algorithm finds the shortest paths between all pairs of vertices in a weighted graph, improving efficiency compared to running single-source algorithms repeatedly.

Finally, we learned about the greedy technique, which builds solutions step by step by choosing the locally optimal option at each stage. Prim’s algorithm, an example of this approach, constructs a minimum spanning tree by repeatedly adding the lowest-cost edge that connects a new vertex.

Overall, this week highlighted different strategies for solving complex optimization and graph problems efficiently.

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