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Add algorithm Breadth-first shortest path #572
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ruppysuppy
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TheAlgorithms:master
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algobytewise:add-BreadthFirstShortestPath
Feb 28, 2021
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,85 @@ | ||
| /* | ||
| Breadth-first approach can be applied to determine the shortest path between two nodes in a graph. It searches the target node among all neighbors of the starting node. Then the process is repeated on the level of the neighbors of the neighbors and so on. | ||
| (See also: https://en.wikipedia.org/wiki/Breadth-first_search ) | ||
| (see also: https://www.koderdojo.com/blog/breadth-first-search-and-shortest-path-in-csharp-and-net-core ) | ||
| */ | ||
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| /* | ||
| Doctests | ||
| > breadthFirstShortestPath(graph, 'C', 'E') | ||
| [ 'C', 'D', 'A', 'B', 'E' ] | ||
| > breadthFirstShortestPath(graph, 'E', 'B') | ||
| [ 'E', 'D', 'A', 'B' ] | ||
| > breadthFirstShortestPath(graph, 'F', 'G') | ||
| [ 'F', 'G' ] | ||
| > breadthFirstShortestPath(graph, 'A', 'G') | ||
| [] | ||
| */ | ||
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| function breadthFirstShortestPath (graph, startNode, targetNode) { | ||
| // check if startNode & targetNode are identical | ||
| if (startNode === targetNode) { | ||
| return [startNode] | ||
| } | ||
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| // visited keeps track of all nodes visited | ||
| const visited = [] | ||
|
Member
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. Use set for keeping track of the visited nodes |
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| // queue contains the paths to be explored in the future | ||
| const initialPath = [startNode] | ||
| const queue = [initialPath] | ||
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| while (queue.length > 0) { | ||
| // start with the queue's first path | ||
| const path = queue.shift() | ||
| const node = path[path.length - 1] | ||
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| // explore this node if it hasn't been visited yet | ||
| if (!visited.includes(node)) { | ||
| // mark the node as visited | ||
| visited.push(node) | ||
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| const neighbors = graph[node] | ||
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| // create a new path in the queue for each neighbor | ||
| for (let i = 0; i < neighbors.length; i++) { | ||
| const newPath = path.concat([neighbors[i]]) | ||
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| // the first path to contain the target node is the shortest path | ||
| if (neighbors[i] === targetNode) { | ||
| return newPath | ||
| } | ||
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| // queue the new path | ||
| queue.push(newPath) | ||
| } | ||
| } | ||
| } | ||
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| // the target node was not reachable | ||
| return [] | ||
| } | ||
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| const graph = { | ||
| A: ['B', 'D'], | ||
| B: ['E'], | ||
| C: ['D'], | ||
| D: ['A'], | ||
| E: ['D'], | ||
| F: ['G'], | ||
| G: [] | ||
| } | ||
| /* | ||
| A <-> B | ||
| ʌ | | ||
| | | | ||
| v v | ||
| C --> D <-- E | ||
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| F --> G | ||
| */ | ||
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| console.log(breadthFirstShortestPath(graph, 'C', 'E')) | ||
| console.log(breadthFirstShortestPath(graph, 'E', 'B')) | ||
| console.log(breadthFirstShortestPath(graph, 'F', 'G')) | ||
| console.log(breadthFirstShortestPath(graph, 'A', 'G')) | ||
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bfs can only be used in case of equi-weighted graph to find the shortest path