Lesson plan
Push–relabel maximum flow algorithm
In mathematical optimization, the push–relabel algorithm (alternatively, preflow–push algorithm) is an algorithm for computing maximum flows in a flow network. The name "push–relabel" comes from the two basic operations used in the algorithm. Throughout its execution, the algorithm maintains a "preflow" and gradually converts it into a maximum flow by moving flow locally between neighboring nodes using push operations under the guidance of an admissible network maintained by relabel operations. In comparison, the Ford–Fulkerson algorithm performs global augmentations that send flow following paths from the source all the way to the sink. The push–relabel algorithm is considered one of the most efficient maximum flow algorithms. The generic algorithm has a strongly polynomial time complexity, which is asymptotically more efficient than the Edmonds–Karp algorithm. Specific variants of the algorithms achieve even lower time complexities. The variant based on the highest label node selection rule has time complexity and is generally regarded as the benchmark for maximum flow algorithms. Subcubic time complexity can be achieved using dynamic trees, although in practice it is less efficient. The push–relabel algorithm has been extended to compute minimum cost flows.…
Article summary
In mathematical optimization, the push–relabel algorithm (alternatively, preflow–push algorithm) is an algorithm for computing maximum flows in a flow network. The name "push–relabel" comes from the two basic operations used in the algorithm. Throughout its execution, the algorithm maintains a "preflow" and gradually converts it into a maximum flow by moving flow locally between neighboring nodes using push operations under the guidance of an admissible network maintained by relabel operations. In comparison, the Ford–Fulkerson algorithm performs global augmentations that send flow following paths from the source all the way to the sink. The push–relabel algorithm is considered one of the most efficient maximum flow algorithms. The generic algorithm has a strongly polynomial time complexity, which is asymptotically more efficient than the Edmonds–Karp algorithm. Specific variants of the algorithms achieve even lower time complexities. The variant based on the highest label node selection rule has time complexity and is generally regarded as the benchmark for maximum flow algorithms. Subcubic time complexity can be achieved using dynamic trees, although in practice it is less efficient. The push–relabel algorithm has been extended to compute minimum cost flows.…
Key claims
- publication date: 1974 — source: Wikipedia · confidence 0.95
Discussion questions
- Summarise the article in your own words. Which single claim would you verify first, and why?
- The record states that the publication date is "1974". What evidence would count against this claim?
- Which claim in this article is most likely to be revised as the sources update? How would you check its current status?
- If two sources disagreed about one of these facts, what would you need in order to trust one over the other?
Bibliography
- Wikipedia https://en.wikipedia.org/w/index.php?oldid=1378823707
Key claims and bibliography are generated from the same tracked claims and sources as the article page.