Exploiting sparsity for the min k-partition problem
- The minimum k-partition problem is a challenging combinatorial problem with a diverse set of applications ranging from telecommunications to sports scheduling. It generalizes the max-cut problem and has been extensively studied since the late sixties. Strong integer formulations proposed in the literature suffer from a large number of constraints and variables. In this work, we introduce two more compact integer linear and semidefinite reformulations that exploit the sparsity of the underlying graph and develop theoretical results leveraging the power of chordal decomposition. Numerical experiments show that the new formulations improve upon state-of-the-art.
Metadaten| Author: | Guanglei Wang, Hassan Hijazi |
|---|
| DOI: | https://doi.org/10.1007/s12532-019-00165-3 |
|---|
| ISSN: | 1867-2949 |
|---|
| Parent Title (English): | Mathematical Programming Computation |
|---|
| Publisher: | Springer Science and Business Media LLC |
|---|
| Document Type: | Article |
|---|
| Language: | English |
|---|
| Year of Completion: | 2019 |
|---|
| Release Date: | 2024/04/08 |
|---|
| Tag: | Software; Theoretical Computer Science |
|---|
| Volume: | 12 |
|---|
| Issue: | 1 |
|---|
| Page Number: | 22 |
|---|
| First Page: | 109 |
|---|
| Last Page: | 130 |
|---|
| Mathematical Programming Computation : | MPC 2020 - Issue 1 |
|---|
