The Jonker-Volgenant algorithm is much faster than the famous Hungarian algorithm for the Linear Assignment Problem (LAP). This Matlab implementation is modified from the original C++ code made by Roy Jonker, one of the inventors of the algorithm. It is about 10 times faster than the munkres code (v2.2) of the author. It can solve a 1000 x 1000 problem in about 3 seconds in a normal Intel Centrino processor.
V1.1 returns the dual variables and the reduced cost matrix as well.
V1.2 can deal with nonsquare assignment problems.
V2.0 is faster for problems with a large range of costs.
V2.1 includes an option to change the cost resolution to improve performance for some problems.
v2.2 removes a small bug to avoid NAN for 1x1 case.
v2.3 removes a small bug to handle a cost matrix with all inf's.
v2.4 fixes a bug associated with resolution to address the known problem of the algorithm.
v3.0 fixes a bug introduced since v2.0.
Reference:
R. Jonker and A. Volgenant, "A shortest augmenting path algorithm for dense and spare linear assignment problems", Computing, Vol. 38, pp. 325-340, 1987.
引用
Yi Cao (2024). LAPJV - Jonker-Volgenant Algorithm for Linear Assignment Problem V3.0 (https://www.mathworks.com/matlabcentral/fileexchange/26836-lapjv-jonker-volgenant-algorithm-for-linear-assignment-problem-v3-0), MATLAB Central File Exchange. に取得済み.
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ヒントを得たファイル: Munkres Assignment Algorithm, Hungarian Algorithm for Linear Assignment Problems (V2.3)
ヒントを与えたファイル: Hungarian Algorithm for Linear Sum Assignment Problem, K-Best Assignment Algorithm, Faster Jonker-Volgenant Assignment Algorithm
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Start Hunting!バージョン | 公開済み | リリース ノート | |
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1.14.0.0 | A bug introduced since v2.0 is fixed |
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1.12.0.0 | A bugg fix |
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1.11.0.0 | Big fix |
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1.10.0.0 | update description |
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1.9.0.0 | Removes a small bug to handle a cost matrix with all inf's. |
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1.8.0.0 | v2.2 removes a small bug to avoid NAN for 1x1 case. |
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1.7.0.0 | option to change cost resolution. |
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1.6.0.0 | V2.0 is faster for problems with a large range of cost values. |
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1.5.0.0 | update the file |
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1.4.0.0 | V1.2 is able to deal with nonsquare cases. |
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1.3.0.0 | Version 1.1 returns dual variables and reduced cost matrix |
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1.2.0.0 | a bug fixed |
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1.1.0.0 | update descriptions |
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1.0.0.0 |