Min-Max quickest path problems

Authors:
Stefan Ruzika;Markus Thiemann
Affiliations:
University of Kaiserslautern, Postbox 3049, 67653 Kaiserslautern, Germany;University of Kaiserslautern, Postbox 3049, 67653 Kaiserslautern, Germany
Venue:
Networks
Year:
2012

Citing 12
Cited 0

Combinatorial optimization: algorithms and complexity

Combinatorial optimization: algorithms and complexity
The quickest path problem

Computers and Operations Research
Algorithms for the quickest path problem and the enumeration of quickest paths

Computers and Operations Research
The all-pairs quickest path problem

Information Processing Letters
Finding the k quickest simple paths in a network

Information Processing Letters
On the robust shortest path problem

Computers and Operations Research
Extend the quickest path problem to the system reliability evaluation for a stochastic-flow network

Computers and Operations Research
On the approximability of trade-offs and optimal access of Web sources

FOCS '00 Proceedings of the 41st Annual Symposium on Foundations of Computer Science
Multicriteria Optimization

Multicriteria Optimization
Multiobjective Optimization: Improved FPTAS for Shortest Paths and Non-Linear Objectives with Applications

Theory of Computing Systems
General approximation schemes for min-max (regret) versions of some (pseudo-)polynomial problems

Discrete Optimization
An algorithm for the quickest path problem

Operations Research Letters

Quantified Score

Hi-index	0.00

Visualization

Abstract

In a dynamic network, the quickest path problem asks for a path such that a given amount of flow can be sent from source to sink via this path in minimal time. In practical settings, for example, in evacuation or transportation planning, the problem parameters might not be known exactly a priori. It is therefore of interest to consider robust versions of these problems in which travel times and/or capacities of arcs depend on a certain scenario. In this article, min–max versions of robust quickest path problems are investigated and, depending on their complexity status, exact algorithms or fully polynomial-time approximation schemes are proposed. © 2012 Wiley Periodicals, Inc. NETWORKS, 2012 © 2012 Wiley Periodicals, Inc.