mention forward/reverse auction algorithms
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readme.md
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readme.md
@@ -57,10 +57,6 @@ a pairSEQ experiment is bipartite with integer weights, this algorithm seems ide
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fairly new algorithm, and not yet implemented by the graph theory library used in this simulator (JGraphT), nor has the author had
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fairly new algorithm, and not yet implemented by the graph theory library used in this simulator (JGraphT), nor has the author had
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time to implement it himself.
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time to implement it himself.
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There have been some studies which show that [auction algorithms](https://en.wikipedia.org/wiki/Auction_algorithm) for the assignment problem can have superior performance in
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real-world implementations, due to their simplicity, than more complex algorithms with better theoretical asymptotic
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performance. But, again, there is no such algorithms implemented by JGraphT, nor has the author yet had time to implement one.
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So this program instead uses the [Fibonacci heap](https://en.wikipedia.org/wiki/Fibonacci_heap) based algorithm of Fredman and Tarjan (1987) (essentially
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So this program instead uses the [Fibonacci heap](https://en.wikipedia.org/wiki/Fibonacci_heap) based algorithm of Fredman and Tarjan (1987) (essentially
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[the Hungarian algorithm](https://en.wikipedia.org/wiki/Hungarian_algorithm) augmented with a more efficeint priority queue) which has a worst-case
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[the Hungarian algorithm](https://en.wikipedia.org/wiki/Hungarian_algorithm) augmented with a more efficeint priority queue) which has a worst-case
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runtime of **O(n (n log(n) + m))**. The algorithm is implemented as described in Melhorn and Näher (1999). (The simulator
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runtime of **O(n (n log(n) + m))**. The algorithm is implemented as described in Melhorn and Näher (1999). (The simulator
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@@ -75,6 +71,15 @@ be balanced assignment problems, in practice sequence dropout can cause them to
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the Hungarian algorithm, graph doubling--which could be challenging with the computational resources available to the
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the Hungarian algorithm, graph doubling--which could be challenging with the computational resources available to the
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author--has not yet been necessary.
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author--has not yet been necessary.
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There have been some studies which show that [auction algorithms](https://en.wikipedia.org/wiki/Auction_algorithm) for the assignment problem can have superior performance in
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real-world implementations, due to their simplicity, than more complex algorithms with better theoretical asymptotic
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performance. The author has implemented a basic forward auction algorithm, which produces optimal assignment for unbalanced bipartite graphs with
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integer weights. To allow for unbalanced assignment, this algorithim eschews epsilon-scaling,
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and as a result is prone to "bidding-wars" which increase run time, making it less efficient than the implementation of
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the Fredman-Tarjan algorithm in JGraphT. A forward/reverse auction algorithm as developed by Bertsekas and Castañon
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should be able to handle unbalanced (or, as they call it, asymmetric) assignment much more efficiently, but has yet to be
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implemented.
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The relative time/space efficiencies of BiGpairSEQ when backed by different MWM algorithms remains an open problem.
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The relative time/space efficiencies of BiGpairSEQ when backed by different MWM algorithms remains an open problem.
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## THE BiGpairSEQ ALGORITHM
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## THE BiGpairSEQ ALGORITHM
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