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Simplest Intuitive Proof of Dijkstra’s Shortest path Algorithm

 Simplest Intuitive Proof of Dijkstra’s Shortest path  Algorithm


Dijkstra's shortest path algorithm is a fundamental algorithm used to find the shortest paths from a source node to all other nodes in a weighted graph. While it may be challenging to provide the simplest and most intuitive proof in a text format, I can give you a high-level overview of the algorithm's intuition and correctness.

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The intuition behind Dijkstra's algorithm can be summarized as follows:


Initialization: Start at the source node and set its distance to 0. Set the distances to all other nodes to infinity initially. Create an empty set (or priority queue) to keep track of the nodes whose shortest distances have been determined.

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Greedy Selection: Repeatedly select the node with the smallest distance from the set of unprocessed nodes. Initially, this will be the source node.

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Relaxation: For the selected node, consider all its neighbors (nodes connected by edges). For each neighbor, calculate the total distance from the source node through the selected node. If this distance is shorter than the neighbor's current distance, update the neighbor's distance to this shorter distance.


Repeat: Repeat steps 2 and 3 until you have processed all nodes or until the destination node's distance cannot be improved further.

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Termination: When all nodes have been processed or when the destination node's distance cannot be improved further, the algorithm terminates. The distances to all nodes represent the shortest path distances from the source node.





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Now, for a simplified proof of correctness:


Dijkstra's algorithm is based on the principle of "greedy choice." At each step, it selects the node with the smallest tentative distance, which guarantees that the algorithm explores shorter paths before longer ones.

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The algorithm maintains a set of explored nodes and always selects the unexplored node with the smallest tentative distance. This guarantees that when the destination node is reached, its distance is indeed the shortest possible.

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The relaxation step ensures that if there's a shorter path to a node through the currently selected node, the algorithm updates the node's distance accordingly. This ensures that once a node is selected, its distance is final and represents the shortest path to that node.

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The algorithm terminates when all nodes have been processed or when the destination node's distance cannot be improved further. At this point, all shortest path distances from the source node to all other nodes have been found.

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Dijkstra's algorithm is guaranteed to find the correct shortest paths as long as it is applied to graphs with non-negative edge weights. If there are negative edge weights, the Bellman-Ford algorithm is a more suitable choice.

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