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For Researchers · Bipartite Matching

Bipartite Matching for a routing table

Built for researchers prototyping or validating an idea. Prototype fast, reproduce exactly, and share a citable, interactive version of your model. Simulate a routing table live below — adjust the inputs and watch it respond, right in your browser.

Bipartite MatchingLive

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Maximum bipartite matching pairs items from two groups — workers to jobs, students to schools, organs to recipients — so that as many valid pairings as possible are made, with no one assigned twice. Kuhn's algorithm repeatedly finds augmenting paths that improve the matching. The green edges are the optimal assignment.

▶ Run in Python

Data Inspector

Matched pairs0
Max possible6
Methodaugmenting paths

Governing equation

Reading this result: Only 0 of 6 paired: at 40% density the graph is too sparse, so many workers have no eligible job and augmenting paths run out early.

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Frequently asked questions

Is this good for researchers?
Yes — this version of "Bipartite Matching for a routing table" is framed for researchers prototyping or validating an idea. Prototype fast, reproduce exactly, and share a citable, interactive version of your model.
Do I need to install anything?
No. It runs in any modern browser, free, with no account required.