Bottleneck flows in networks

TL;DR

This paper reviews the bottleneck network flow problem (BNFP), showing it can be efficiently solved using maximum flow algorithms, and presents improved algorithms for special cases like unit capacities and simple graphs.

Contribution

It demonstrates that BNFP can be solved as a sequence of maximum flow problems and introduces faster algorithms for unit capacity networks and simple graphs.

Findings

BNFP solvable via $O( ext{log } n)$ maximum flow iterations.

Improved algorithm for BNFP on unit capacity networks with complexity $O( ext{min}igrace{m(n ext{log } n)^{2/3}, m^{3/2} ext{log } n^{1/2}}ig)$.

BNFP on simple graphs solvable in $O(m ext{sqrt } n ext{log } n)$ time.

Abstract

The bottleneck network flow problem (BNFP) is a generalization of several well-studied bottleneck problems such as the bottleneck transportation problem (BTP), bottleneck assignment problem (BAP), bottleneck path problem (BPP), and so on. In this paper we provide a review of important results on this topic and its various special cases. We observe that the BNFP can be solved as a sequence of $O(\log n)$ maximum flow problems. However, special augmenting path based algorithms for the maximum flow problem can be modified to obtain algorithms for the BNFP with the property that these variations and the corresponding maximum flow algorithms have identical worst case time complexity. On unit capacity network we show that BNFP can be solved in $O(\min \{{m(n\log n)}^{{2/3}}, m^{{3/2}}\sqrt{\log n}\})$. This improves the best available algorithm by a factor of $\sqrt{\log n}$. On unit capacity simple graphs, we show that BNFP can be solved in $O(m \sqrt {n \log n})$ time. As a consequence we have an $O(m \sqrt {n \log n})$ algorithm for the BTP with unit arc capacities.