Published October 3, 2023 | Version v1
Publication

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

Created:
January 10, 2024
Modified:
January 10, 2024