On approximate data reduction for the Rural Postman Problem: Theory and experiments. van Bevern, R., Fluschnik, T., & Tsidulko, O. Networks, 76(4):485-508, 2020.
On approximate data reduction for the Rural Postman Problem: Theory and experiments [link]Preprint  On approximate data reduction for the Rural Postman Problem: Theory and experiments [link]Poster  On approximate data reduction for the Rural Postman Problem: Theory and experiments [link]Slides  On approximate data reduction for the Rural Postman Problem: Theory and experiments [link]Code  doi  abstract   bibtex   
Given a graph G=(V,E) with edge weights ω:E→N∪0 and a subset R⊆E of required edges, the Rural Postman Problem (RPP) is to find a closed walk W* of minimum weight ω(W*) containing all edges of R. We prove that RPP is WK[1]-complete parameterized by the number and cost d=ω(W^*)-ω(R)+|W*|-|R| of edges traversed additionally to the required ones, that is, presumably cannot be polynomial-time reduced to solving instances of size polynomial in d. In contrast, denoting by b≤2d the number of vertices incident to an odd number of edges of R and by c≤d the number of connected components formed by the edges in R, we show how to reduce any RPP instance I to an RPP instance I' with 2b+O(c/ε) vertices in O(n³) time so that any α-approximate solution for I' gives an α(1+ε)-approximate solution for I, for any α≥1 and ε>0. That is, we provide a polynomial-size approximate kernelization scheme (PSAKS). We make first steps towards a PSAKS for the parameter c.
@article{BFT20b,
  author =	 {Ren{\'{e}} van Bevern and Till Fluschnik and Oxana
                  Tsidulko},
  title =	 {On approximate data reduction for the {Rural Postman
                  Problem}: Theory and experiments},
  year =	 {2020},
  date =	 {2020-11-02},
  journal =	 {Networks},
  url_Preprint = {https://arxiv.org/abs/1812.10131},
  url_Poster =
                  {https://figshare.com/articles/poster/On_approximate_data_reduction_for_the_Rural_Postman_Problem/13058969},
  url_Slides =
                  {https://www.researchgate.net/publication/348297308_On_approximate_approximate_data_reduction_for_the_Rural_Postman_Problem_Theory_and_Experiments},
  doi =		 {10.1002/net.21985},
  volume =	 76,
  number =	 4,
  pages =	 {485-508},
  url_Code =	 {https://gitlab.com/rvb/rpp-psaks},
  abstract =	 {Given a graph G=(V,E) with edge weights ω:E→N∪{0}
                  and a subset R⊆E of required edges, the Rural
                  Postman Problem (RPP) is to find a closed walk W* of
                  minimum weight ω(W*) containing all edges of R. We
                  prove that RPP is WK[1]-complete parameterized by
                  the number and cost d=ω(W^*)-ω(R)+|W*|-|R| of edges
                  traversed additionally to the required ones, that
                  is, presumably cannot be polynomial-time reduced to
                  solving instances of size polynomial in d. In
                  contrast, denoting by b≤2d the number of vertices
                  incident to an odd number of edges of R and by c≤d
                  the number of connected components formed by the
                  edges in R, we show how to reduce any RPP instance I
                  to an RPP instance I' with 2b+O(c/ε) vertices in
                  O(n³) time so that any α-approximate solution for I'
                  gives an α(1+ε)-approximate solution for I, for any
                  α≥1 and ε>0. That is, we provide a polynomial-size
                  approximate kernelization scheme (PSAKS). We make
                  first steps towards a PSAKS for the parameter c.}
}

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