Abstract

In a digraph with a source and several destination nodes with associated demands, an unsplittable flow routes each demand along a single path from the common source to its destination. Given some flow x that is not necessarily unsplittable but satisfies all demands, it is a natural question to ask for an unsplittable flow y that does not deviate from x by too much, i.e., y_aapprox x_a for all arcs a. Twenty years ago, in a landmark paper, Dinitz et al. (Combinatorica 19:17–41, 1999) proved that there exists an unsplittable flow y such that y_ale x_a+d_{max } for all arcs a, where d_{max } denotes the maximum demand value. Our first contribution is a considerably simpler one-page proof for this classical result, based upon an entirely new approach. Secondly, using a subtle variant of this approach, we obtain a new result: There is an unsplittable flow y such that y_age x_a-d_{max } for all arcs a. Finally, building upon an iterative rounding technique previously introduced by Kolliopoulos and Stein (SIAM J Comput 31:919–946, 2002) and Skutella (Math Program 91:493–514, 2002), we prove existence of an unsplittable flow that simultaneously satisfies the upper and lower bounds for the special case when demands are integer multiples of each other. For arbitrary demand values, we prove the weaker simultaneous bounds x_a/2-d_{max }le y_ale 2x_a+d_{max } for all arcs a.

Highlights

  • Ever since the seminal work of Ford and Fulkerson [6] network flows belong to the most important and fundamental class of problems in combinatorial optimization and mathematical programming

  • The central result in the seminal paper of Dinitz et al [4] is the following theorem on single source unsplittable flows, where the maximum demand value is denoted by dmax := max{d1, . . . , dk }

  • For a path Q and two nodes v, w ∈ V lying on path Q, the v-w-subpath of Q is denoted by Q|[v,w]

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Summary

Introduction

Ever since the seminal work of Ford and Fulkerson [6] network flows belong to the most important and fundamental class of problems in combinatorial optimization and mathematical programming. We refer to the classical textbook [1] by Ahuja, Magnanti, and Orlin as well as the very recent new textbook [17] by Williamson on the topic

Problem setting and notation
Single source unsplittable flows
Related literature
Contribution and outline
Preliminaries
A short proof of the Dinitz–Garg–Goemans Theorem
A UBP augmentation step for an unsplittable flow y is defined as follows
Unsplittable flows with arc-wise lower bounds
A proof for unsplittable flows satisfying arc-wise lower bounds
Problem variants for unsplittable flows satisfying arc-wise lower bounds
Combining lower and upper bounds
This implies that x
Conclusion
A An upper bound on the number of UBP augmentation steps
B Unsplittable flows and scheduling
Full Text
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