The breadth-first search (BFS) algorithm is a method that allows programs to perform a search using a level-based approach to address problems. Before a system can proceed to the next step, it must solve the first part of the problem.
It uses a searching tree or graph data structure to find the shortest path from a given source to other sources. Before moving on to the next data source, however, it must fully exhaust the available information in the current source.
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How Does the Breadth-First Search Algorithm Work?
Here is an illustration so you can understand how the breadth-first search algorithm works:
The breadth-first search algorithm works on a process in cycles.
In the diagram, the first cycle of the process starts from 1, then proceeds to 2, then 5. From 5, it moves to and ends at 9.
The second cycle begins with 1, then proceeds to 2. From 2, it will move to 5. From there, it moves on to and ends at 10 (instead of 9 in the first cycle).
The third cycle begins with 1 then moves to 2. From 2, it moves to and ends at 6 (instead of 5 in the first and second cycles).
The fourth cycle starts from 1, then moves and ends at 3 (instead of 2 in the first to third cycles).
The fifth cycle begins with 1, then proceeds to 4 (instead of 2 or 3), then 7 and, finally, 11.
The sixth cycle starts from 1, then 4, then 7, and, finally, 12 (instead of 11 in the fifth cycle).
The seventh and final cycle begins with 1, moves to 4, then, finally, 8.
As the seven cycles show, all steps must be completed before the process ends.
What Are the Advantages and Disadvantages of Using the Breadth-First Search Algorithm?
The breadth-first search algorithm is often used in artificial intelligence (AI) because it can:
- Find the shortest path between nodes or steps
- Identify the most optimal solution path to addressing a problem
- Use all available paths since the search is done in cycles if users want to be thorough and exhaust all possibilities
- Determine the closest goal that requires the shortest amount of time for users in search of answers fast
But it also comes with some disadvantages, such as consuming considerable memory space. When used for more complex processes, the paths become longer, making it very time-consuming.
What Technologies Use the Breadth-First Search Algorithm?
The breadth-first search algorithm is currently used in:
- Peer-to-peer (P2P) networks: P2P networks, particularly BitTorrent, use the breadth-first search algorithm to ensure it searches all available files exhaustively before pointing users to those that will require the shortest time for download or upload.
- Search engine crawlers: For use in search engine crawlers, a system should have built-in indices connected to the source page. All the links in the index that point to available pages should be connected to the source. Only after identification are the web pages crawled.
- Social media platforms: Social media networks such as Facebook, Twitter, and Instagram use the breadth-first search algorithm to show people results that are the most directly connected to a post’s original source.
The breadth-first search algorithm is commonly used for operations that can benefit from identifying the shortest solution despite several alternatives or paths. Many users, however, limit the algorithm’s use to some small-scale operations because it consumes a lot of memory.