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Main Authors: Kaymakov, Kirill V., Malyshev, Dmitry S.
Format: Preprint
Published: 2024
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Online Access:https://arxiv.org/abs/2408.09443
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author Kaymakov, Kirill V.
Malyshev, Dmitry S.
author_facet Kaymakov, Kirill V.
Malyshev, Dmitry S.
contents The tolerance of an element of a combinatorial optimization problem with respect to a given optimal solution is the maximum change, i.e., decrease or increase, of its cost, such that this solution remains optimal. The bottleneck path problem, for given an edge-capacitated graph, a source, and a target, is to find the $\max$-$\min$ value of edge capacities on paths between the source and the target. For any given sample of this problem with $n$ vertices and $m$ edges, there is known the Ramaswamy-Orlin-Chakravarty's algorithm to compute an optimal path and all tolerances with respect to it in $O(m+n\log n)$ time. In this paper, for any in advance given $(n,m)$-network with distinct edge capacities and $k$ source-target pairs, we propose an $O\Big(m α(m,n)+\min\big((n+k)\log n,km\big)\Big)$-time preprocessing, where $α(\cdot,\cdot)$ is the inverse Ackermann function, to find in $O(k)$ time all $2k$ tolerances of an arbitrary edge with respect to some $\max\min$ paths between the paired sources and targets. To find both tolerances of all edges with respect to those optimal paths, it asymptotically improves, for some $n,m,k$, the Ramaswamy-Orlin-Chakravarty's complexity $O\big(k(m+n\log n)\big)$ up to $O(mα(n,m)+km)$.
format Preprint
id arxiv_https___arxiv_org_abs_2408_09443
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Efficient Online Sensitivity Analysis For The Injective Bottleneck Path Problem
Kaymakov, Kirill V.
Malyshev, Dmitry S.
Data Structures and Algorithms
Discrete Mathematics
The tolerance of an element of a combinatorial optimization problem with respect to a given optimal solution is the maximum change, i.e., decrease or increase, of its cost, such that this solution remains optimal. The bottleneck path problem, for given an edge-capacitated graph, a source, and a target, is to find the $\max$-$\min$ value of edge capacities on paths between the source and the target. For any given sample of this problem with $n$ vertices and $m$ edges, there is known the Ramaswamy-Orlin-Chakravarty's algorithm to compute an optimal path and all tolerances with respect to it in $O(m+n\log n)$ time. In this paper, for any in advance given $(n,m)$-network with distinct edge capacities and $k$ source-target pairs, we propose an $O\Big(m α(m,n)+\min\big((n+k)\log n,km\big)\Big)$-time preprocessing, where $α(\cdot,\cdot)$ is the inverse Ackermann function, to find in $O(k)$ time all $2k$ tolerances of an arbitrary edge with respect to some $\max\min$ paths between the paired sources and targets. To find both tolerances of all edges with respect to those optimal paths, it asymptotically improves, for some $n,m,k$, the Ramaswamy-Orlin-Chakravarty's complexity $O\big(k(m+n\log n)\big)$ up to $O(mα(n,m)+km)$.
title Efficient Online Sensitivity Analysis For The Injective Bottleneck Path Problem
topic Data Structures and Algorithms
Discrete Mathematics
url https://arxiv.org/abs/2408.09443