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KRHow do navigation apps find the quickest route? This video shows the power of **Bidirectional Breadth-First Search (BFS) in action, a key algorithm behind fast and efficient pathfinding.
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GHBreadth First Search (BFS)
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Breadth First Search (BFS) is a fundamental graph traversal algorithm. It involves visiting all the connected nodes of a graph in a level-by-level manner. In this article, we will look into the concept of BFS and how it can be applied to graphs effectively.
Breadth First Search (BFS) for a Graph:
Breadth First Search (BFS) is a graph traversal algorithm that explores all the vertices in a graph at the current depth before moving on to the vertices at the next depth level. It starts at a specified vertex and visits all its neighbors before moving on to the next level of neighbors. BFS is commonly used in algorithms for pathfinding, connected components, and shortest path problems in graphs.
Relation between BFS for Graph and BFS for Tree:
Breadth-First Traversal (BFS) for a graph is similar to the Breadth-First Traversal of a tree.
The only catch here is, that, unlike trees, graphs may contain cycles, so we may come to the same node again. To avoid processing a node more than once, we divide the vertices into two categories:
Visited and
Not visited.
A boolean visited array is used to mark the visited vertices. For simplicity, it is assumed that all vertices are reachable from the starting vertex. BFS uses a queue data structure for traversal.
Breadth First Search (BFS) for a Graph Algorithm:
Let’s discuss the algorithm for the BFS:
Initialization: Enqueue the starting node into a queue and mark it as visited.
Exploration: While the queue is not empty:
Dequeue a node from the queue and visit it (e.g., print its value).
For each unvisited neighbor of the dequeued node:
Enqueue the neighbor into the queue.
Mark the neighbor as visited.
Termination: Repeat step 2 until the queue is empty.
This algorithm ensures that all nodes in the graph are visited in a breadth-first manner, starting from the starting node.
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COBFS vs DFS — wave vs dive 🔊
BFS expands uniformly, layer by layer. Guarantees shortest path.
DFS commits deep, backtracks when stuck. Finds a path faster — but not always optimal.
Same dungeon. Different philosophies. Watch them race.
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VI👇 BFS vs DFS (Graph / Tree Traversal)
🔵 BFS (Breadth First Search)
Explores level by level.
Uses a Queue.
Best for shortest path in unweighted graphs.
🟣 DFS (Depth First Search)
Explores depth first, then backtracks.
Uses a Stack / Recursion.
Best for path exploration & cycle detection.
⏱ Time Complexity: O(V + E)
📌 Same complexity, different approach
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