The Minimum Birkhoff Decomposition problem seeks to express a doubly stochastic matrix as a minimal convex combination of permutation matrices. This problem arises in various applications including assignment problems, scheduling, and quantum physics.
Definitions:
- A doubly stochastic matrix
$D \in \mathbb{R}^{n \times n}$ has non-negative entries where all rows and columns sum to one - A permutation matrix
$P_i$ is a doubly stochastic matrix with binary entries - Let
$P_1, \ldots, P_{n!}$ denote all possible$n \times n$ permutation matrices
Optimization Problem:
For a given doubly stochastic matrix
subject to: $$ D = \sum_{i=1}^{n!} \lambda_i P_i, \qquad \sum_{i=1}^{n!} \lambda_i = 1 $$
where
Goal: Find the smallest number of permutation matrices whose convex combination equals
- instances/ - Doubly stochastic matrices to decompose
- models/ - Mathematical model formulations
- solutions/ - Optimal or best-known solutions
- check/ - Solution verification tools
- misc/ - Utility scripts and generators
- submissions/ - Community solution submissions
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Kulkarni, J., Lee, E., Singh, M. (2017). Minimum Birkhoff-von Neumann Decomposition. In International Conference on Integer Programming and Combinatorial Optimization (pp. 343-354). Springer International Publishing, Cham.
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Dufossé, F., Uçar, B. (2016). Notes on Birkhoff–von Neumann decomposition of doubly stochastic matrices. Linear Algebra and its Applications, 497, pp.108-115.