Constrained Flows in Networks
- Others:
- Algorithmes, Graphes et Combinatoire (LIRMM | ALGCO) ; Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier (LIRMM) ; Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)
- University of Southern Denmark (SDU)
- Combinatorics, Optimization and Algorithms for Telecommunications (COATI) ; Inria Sophia Antipolis - Méditerranée (CRISAM) ; Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-COMmunications, Réseaux, systèmes Embarqués et Distribués (Laboratoire I3S - COMRED) ; Laboratoire d'Informatique, Signaux, et Systèmes de Sophia Antipolis (I3S) ; Université Nice Sophia Antipolis (1965 - 2019) (UNS)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA)-Université Nice Sophia Antipolis (1965 - 2019) (UNS)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA)-Laboratoire d'Informatique, Signaux, et Systèmes de Sophia Antipolis (I3S) ; Université Nice Sophia Antipolis (1965 - 2019) (UNS)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA)-Université Nice Sophia Antipolis (1965 - 2019) (UNS)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA)
- ANR-19-CE48-0013,DIGRAPHS,Digraphes(2019)
- ANR-17-EURE-0004,UCA DS4H,UCA Systèmes Numériques pour l'Homme(2017)
Description
The support of a flow $x$ in a network is the subdigraph induced by the arcs $ij$ for which $x_{ij}>0$. We discuss a number of results on flows in networks where we put certain restrictions on structure of the support of the flow. Many of these problems are NP-hard because they generalize linkage problems for digraphs. For example deciding whether a network ${\cal N}=(D,s,t,c)$ has a maximum flow $x$ such that the maximum out-degree of the support $D_x$ of $x$ is at most 2 is NP-complete as it contains the 2-linkage problem as a very special case. Another problem which is NP-complete for the same reason is that of deciding the maximum flow we can send from $s$ to $t$ along 2 paths (called a maximum 2-path-flow) in ${\cal N}$. Baier et al. (2005) gave a polynomial algorithm which finds a 2-path-flow $x$ whose value is at least $\frac{2}{3}$ of the value of a optimum 2-path-flow. This is best possible unless P=NP. They also obtained a $\frac{2}{p}$-approximation for the maximum value of a $p$-path-flow for every $p\geq 2$. In this paper we give an algorithm which gets within a factor $\frac{1}{H(p)}$ of the optimum solution, where $H(p)$ is the $p$'th harmonic number ($H(p) \sim \ln(p)$). This improves the approximation bound due to Baier et al. when $p\geq 5$. We show that in the case where the network is acyclic, we can find a maximum $p$-path-flow in polynomial time for every $p$. We determine the complexity of a number of related problems concerning the structure of flows. For the special case of acyclic digraphs, some of the results we obtain are in some sense best possible.
Additional details
- URL
- https://inria.hal.science/hal-04379871
- URN
- urn:oai:HAL:hal-04379871v1
- Origin repository
- UNICA