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README.md

03 - Minimum Birkhoff Decomposition

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Overview

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.

Problem Description

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 $D$, find:

$$ \underset{\lambda_i \in [0,1]}{\text{minimize}} \qquad \sum_{i=1}^{n!} |\lambda_i|^0 $$

subject to: $$ D = \sum_{i=1}^{n!} \lambda_i P_i, \qquad \sum_{i=1}^{n!} \lambda_i = 1 $$

where $0^0 = 0$ by convention.

Goal: Find the smallest number of permutation matrices whose convex combination equals $D$.

Directory Contents

  • 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

References

  1. 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.

  2. Dufossé, F., Uçar, B. (2016). Notes on Birkhoff–von Neumann decomposition of doubly stochastic matrices. Linear Algebra and its Applications, 497, pp.108-115.