## Abstract

A key result in the field of kernelization, a subfield of parameterized complexity, states that the classic Disjoint Cycle Packing problem, i.e., finding k vertex disjoint cycles in a given graph G, admits no polynomial kernel unless NP ⊆ coNP/poly. However, very little is known about this problem beyond the aforementioned kernelization lower bound (within the parameterized complexity framework). In the hope of clarifying the picture and better understanding the types of constraints that separate kernelizable from nonkernelizable variants of Disjoint Cycle Packing, we investigate two relaxations of the problem. The first variant, which we call Almost Disjoint Cycle Packing, introduces a global relaxation parameter t. That is, given a graph G and integers k and t, the goal is to find at least k distinct cycles such that every vertex of G appears in at most t of the cycles. The second variant, Pairwise Disjoint Cycle Packing, introduces a local relaxation parameter, and we seek at least k distinct cycles such that every two cycles intersect in at most t vertices. While the Pairwise Disjoint Cycle Packing problem admits a polynomial kernel for all t ≥ 1, the kernelization complexity of Almost Disjoint Cycle Packing reveals an interesting spectrum of upper and lower bounds. In particular, for t = ^{k} _{c} , where c could be a function of k, we obtain a kernel of size O(2^{c} ^{2}k^{7+c} log^{3} k) whenever c ∈ o( √ k). Thus the kernel size varies from being subexponential when c ∈ o( √ k), to quasi-polynomial when c ∈ o(logℓ k), ℓ ∈ R_{+}, and polynomial when c ∈ O(1). We complement these results for Almost Disjoint Cycle Packing by showing that the problem does not admit a polynomial kernel whenever t ∈ O(kε) for any 0 ≤ ε < 1, unless NP ⊆ coNP/poly.

Original language | English |
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Pages (from-to) | 1619-1643 |

Number of pages | 25 |

Journal | SIAM Journal on Discrete Mathematics |

Volume | 32 |

Issue number | 3 |

DOIs | |

State | Published - 1 Jan 2018 |

Externally published | Yes |

## Keywords

- Cycle packing
- Kernelization
- Lower bounds
- Parameterized complexity
- Relaxation

## ASJC Scopus subject areas

- General Mathematics