What is the time complexity of Dijkstra's algorithm in Python?
An example of an AI chatbot conversation about Dijkstra's algorithm time complexity in Python.
What is the time complexity of Dijkstra's algorithm in Python?
Dijkstra's algorithm has a time complexity of O(V^2) using a simple array, but it can be improved to O(E + V log V) with a priority queue.
Can you explain the difference between the two complexities?
Sure! O(V^2) is the complexity when using an adjacency matrix, while O(E + V log V) is achieved with a binary heap for the priority queue, making it more efficient for sparse graphs.
What are V and E in this context?
In this context, V represents the number of vertices (nodes) in the graph, and E represents the number of edges (connections) between those vertices.
Are there any scenarios where Dijkstra's algorithm is not suitable?
Yes, Dijkstra's algorithm is not suitable for graphs with negative weight edges. In such cases, the Bellman-Ford algorithm is a better choice.
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