Dijkstra's algorithm is widely used for finding the shortest paths from a single source vertex to all other vertices in a weighted graph. The time complexity of Dijkstra's algorithm depends significantly on the data structure used for the priority queue. Using a simple array or list results in a time complexity of , where is the number of vertices. However, when employing a binary heap (often implemented with a priority queue), the time complexity improves to , where is the number of edges.
Additionally, using more advanced data structures like Fibonacci heaps can reduce the time complexity further to , making it more efficient for sparse graphs. The space complexity of Dijkstra's algorithm is , primarily due to the storage of distance values and the priority queue. Overall, Dijkstra's algorithm is a powerful tool for solving shortest path problems, particularly in graphs with non-negative weights.
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