Greeding matching algorithms, an experimental study
Journal of Experimental Algorithmics (JEA)
Augment or push: a computational study of bipartite matching and unit-capacity flow algorithms
Journal of Experimental Algorithmics (JEA)
Combinatorial Optimization: Theory and Algorithms
Combinatorial Optimization: Theory and Algorithms
Parallel greedy graph matching using an edge partitioning approach
Proceedings of the fourth international workshop on High-level parallel programming and applications
Matching in bipartite graph streams in a small number of passes
SEA'11 Proceedings of the 10th international conference on Experimental algorithms
An experimental comparison of single-sided preference matching algorithms
Journal of Experimental Algorithmics (JEA)
Design, implementation, and analysis of maximum transversal algorithms
ACM Transactions on Mathematical Software (TOMS)
A GPU algorithm for greedy graph matching
Facing the Multicore-Challenge II
A multithreaded algorithm for network alignment via approximate matching
SC '12 Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis
Push-relabel based algorithms for the maximum transversal problem
Computers and Operations Research
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It is a well-established result that improved pivoting in linear solvers can be achieved by computing a bipartite matching between matrix entries and positions on the main diagonal. With the availability of increasingly faster linear solvers, the speed of bipartite matching computations must keep up to avoid slowing down the main computation. Fast algorithms for bipartite matching, which are usually initialized with simple heuristics, have been known for a long time. However, the performance of these algorithms is largely dependent on the quality of the heuristic. We compare combinations of several known heuristics and exact algorithms to find fast combined methods, using real-world matrices as well as randomly generated instances. In addition, we present a new heuristic aimed at obtaining high-quality matchings and compare its impact on bipartite matching algorithms with that of other heuristics. The experiments suggest that its performance compares favorably to the best-known heuristics, and that it is especially suited for application in linear solvers.