### Abstract

In this paper, we propose new exact and approximation algorithms for the weighted matroid intersection problem. Our exact algorithm is faster than previous algorithms when the largest weight is relatively small. Our approximation algorithm delivers a (Formula presented.)-approximate solution with a running time significantly faster than most known exact algorithms. The core of our algorithms is a decomposition technique: we decompose an instance of the weighted matroid intersection problem into a set of instances of the unweighted matroid intersection problem. The computational advantage of this approach is that we can make use of fast unweighted matroid intersection algorithms as a black box for designing algorithms. More precisely, we show that we can solve the weighted matroid intersection problem via solving W instances of the unweighted matroid intersection problem, where W is the largest given weight, assuming that all given weights are integral. Furthermore, we can find a (Formula presented.)-approximate solution via solving (Formula presented.) instances of the unweighted matroid intersection problem, where r is the smaller rank of the two given matroids. Our algorithms make use of the weight-splitting approach of Frank (J Algorithms 2(4):328–336, 1981) and the geometric scaling scheme of Duan and Pettie (J ACM 61(1):1, 2014). Our algorithms are simple and flexible: they can be adapted to special cases of the weighted matroid intersection problem, using specialized unweighted matroid intersection algorithms. In addition, we give a further application of our decomposition technique: we solve efficiently the rank-maximal matroid intersection problem, a problem motivated by matching problems under preferences.

Original language | English |
---|---|

Pages (from-to) | 1-28 |

Number of pages | 28 |

Journal | Mathematical Programming |

DOIs | |

Publication status | Accepted/In press - 2018 Mar 20 |

### Fingerprint

### Keywords

- Approximation algorithms
- Exact algorithms
- Weighted matroid intersection

### ASJC Scopus subject areas

- Software
- Mathematics(all)

### Cite this

*Mathematical Programming*, 1-28. https://doi.org/10.1007/s10107-018-1260-x

**Exact and approximation algorithms for weighted matroid intersection.** / Huang, Chien Chung; Kakimura, Naonori; Kamiyama, Naoyuki.

Research output: Contribution to journal › Article

*Mathematical Programming*, pp. 1-28. https://doi.org/10.1007/s10107-018-1260-x

}

TY - JOUR

T1 - Exact and approximation algorithms for weighted matroid intersection

AU - Huang, Chien Chung

AU - Kakimura, Naonori

AU - Kamiyama, Naoyuki

PY - 2018/3/20

Y1 - 2018/3/20

N2 - In this paper, we propose new exact and approximation algorithms for the weighted matroid intersection problem. Our exact algorithm is faster than previous algorithms when the largest weight is relatively small. Our approximation algorithm delivers a (Formula presented.)-approximate solution with a running time significantly faster than most known exact algorithms. The core of our algorithms is a decomposition technique: we decompose an instance of the weighted matroid intersection problem into a set of instances of the unweighted matroid intersection problem. The computational advantage of this approach is that we can make use of fast unweighted matroid intersection algorithms as a black box for designing algorithms. More precisely, we show that we can solve the weighted matroid intersection problem via solving W instances of the unweighted matroid intersection problem, where W is the largest given weight, assuming that all given weights are integral. Furthermore, we can find a (Formula presented.)-approximate solution via solving (Formula presented.) instances of the unweighted matroid intersection problem, where r is the smaller rank of the two given matroids. Our algorithms make use of the weight-splitting approach of Frank (J Algorithms 2(4):328–336, 1981) and the geometric scaling scheme of Duan and Pettie (J ACM 61(1):1, 2014). Our algorithms are simple and flexible: they can be adapted to special cases of the weighted matroid intersection problem, using specialized unweighted matroid intersection algorithms. In addition, we give a further application of our decomposition technique: we solve efficiently the rank-maximal matroid intersection problem, a problem motivated by matching problems under preferences.

AB - In this paper, we propose new exact and approximation algorithms for the weighted matroid intersection problem. Our exact algorithm is faster than previous algorithms when the largest weight is relatively small. Our approximation algorithm delivers a (Formula presented.)-approximate solution with a running time significantly faster than most known exact algorithms. The core of our algorithms is a decomposition technique: we decompose an instance of the weighted matroid intersection problem into a set of instances of the unweighted matroid intersection problem. The computational advantage of this approach is that we can make use of fast unweighted matroid intersection algorithms as a black box for designing algorithms. More precisely, we show that we can solve the weighted matroid intersection problem via solving W instances of the unweighted matroid intersection problem, where W is the largest given weight, assuming that all given weights are integral. Furthermore, we can find a (Formula presented.)-approximate solution via solving (Formula presented.) instances of the unweighted matroid intersection problem, where r is the smaller rank of the two given matroids. Our algorithms make use of the weight-splitting approach of Frank (J Algorithms 2(4):328–336, 1981) and the geometric scaling scheme of Duan and Pettie (J ACM 61(1):1, 2014). Our algorithms are simple and flexible: they can be adapted to special cases of the weighted matroid intersection problem, using specialized unweighted matroid intersection algorithms. In addition, we give a further application of our decomposition technique: we solve efficiently the rank-maximal matroid intersection problem, a problem motivated by matching problems under preferences.

KW - Approximation algorithms

KW - Exact algorithms

KW - Weighted matroid intersection

UR - http://www.scopus.com/inward/record.url?scp=85046042658&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85046042658&partnerID=8YFLogxK

U2 - 10.1007/s10107-018-1260-x

DO - 10.1007/s10107-018-1260-x

M3 - Article

AN - SCOPUS:85046042658

SP - 1

EP - 28

JO - Mathematical Programming

JF - Mathematical Programming

SN - 0025-5610

ER -