FRACTALS FOR KERNELIZATION LOWER BOUNDS

被引:4
|
作者
Fluschnik, Till [1 ]
Hermelin, Danny [2 ]
Nichterlein, Andre [1 ]
Niedermeier, Rolf [1 ]
机构
[1] TU Berlin, Inst Softwaretech & Theoret Informat, Berlin, Germany
[2] Ben Gurion Univ Negev, Dept Ind Engn & Management, Beer Sheva, Israel
基金
以色列科学基金会;
关键词
parameterized complexity; polynomial-time data reduction; lower bounds; cross-compositions; graph modification problems; interdiction problems; PARAMETERIZED COMPLEXITY;
D O I
10.1137/16M1088740
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
The composition technique is a popular method for excluding polynomial-size problem kernels for NP-hard parameterized problems. We present a new technique exploiting triangle based fractal structures for extending the range of applicability of compositions. Our technique makes it possible to prove new no-polynomial-kernel results for a number of problems dealing with length-bounded cuts. In particular, answering an open question of Golovach and Thilikos [Discrete Optim., 8 (2011), pp. 77-86], we show that, unless NP subset of coNP / poly, the NP-hard LENGTH-BOUNDED EDGE-CUT (LBEC) problem (delete at most k edges such that the resulting graph has no s-t path of length shorter than l) parameterized by the combination of k and l has no polynomial-size problem kernel. Our framework applies to planar as well as directed variants of the basic problems and also applies to both edge and vertex-deletion problems. Along the way, we show that LBEC remains NP-hard on planar graphs, a result which we believe is interesting in its own right.
引用
收藏
页码:656 / 681
页数:26
相关论文
共 50 条
  • [1] Lower Bounds for Kernelization
    Bodlaender, Hans L.
    PARAMETERIZED AND EXACT COMPUTATION, IPEC 2014, 2014, 8894 : 1 - 14
  • [2] Lower bounds on kernelization
    Misra, Neeldhara
    Raman, Venkatesh
    Saurabh, Saket
    DISCRETE OPTIMIZATION, 2011, 8 (01) : 110 - 128
  • [3] Kernelization Lower Bounds Through Colors and IDs
    Dom, Michael
    Lokshtanov, Daniel
    Saurabh, Saket
    ACM TRANSACTIONS ON ALGORITHMS, 2014, 11 (02) : 1 - 20
  • [4] KERNELIZATION LOWER BOUNDS BY CROSS-COMPOSITION
    Bodlaender, Hans L.
    Jansen, Bart M. P.
    Kratsch, Stefan
    SIAM JOURNAL ON DISCRETE MATHEMATICS, 2014, 28 (01) : 277 - 305
  • [5] Parametric duality and kernelization: Lower bounds and upper bounds on kernel size
    Chen, Jianer
    Fernau, Henning
    Kanj, Iyad A.
    Xia, Ge
    SIAM JOURNAL ON COMPUTING, 2007, 37 (04) : 1077 - 1106
  • [6] Parametric duality and kernelization: Lower bounds and upper bounds on kernel size
    Chen, JN
    Fernau, H
    Kanj, IA
    Xia, G
    STACS 2005, PROCEEDINGS, 2005, 3404 : 269 - 280
  • [7] Introducing lop-Kernels: A Framework for Kernelization Lower Bounds
    Araujo, Julio
    Bougeret, Marin
    Campos, Victor
    Sau, Ignasi
    ALGORITHMICA, 2022, 84 (11) : 3365 - 3406
  • [8] Cross-Composition: A New Technique for Kernelization Lower Bounds
    Bodlaender, Hans L.
    Jansen, Bart M. P.
    Kratsch, Stefan
    28TH INTERNATIONAL SYMPOSIUM ON THEORETICAL ASPECTS OF COMPUTER SCIENCE (STACS 2011), 2011, 9 : 165 - 176
  • [9] Introducing lop-Kernels: A Framework for Kernelization Lower Bounds
    Júlio Araújo
    Marin Bougeret
    Victor Campos
    Ignasi Sau
    Algorithmica, 2022, 84 : 3365 - 3406
  • [10] Kernelization Lower Bounds for Finding Constant-Size Subgraphs
    Fluschnik, Till
    Mertzios, George B.
    Nichterlein, Andre
    SAILING ROUTES IN THE WORLD OF COMPUTATION, 2018, 10936 : 183 - 193