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Finding Maximum-Success Disjoint Paths

Authors Aaron Neugebauer , Marie Schmidt

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OASIcs.ATMOS.2026.8.pdf
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Subject Classification

ACM Subject Classification
  • Applied computing → Operations research
  • Mathematics of computing → Graph theory
  • Mathematics of computing → Graph algorithms
  • Mathematics of computing → Quasiconvex programming and unimodality
  • Mathematics of computing → Integer programming
  • Theory of computation → Shortest paths
  • Mathematics of computing → Approximation algorithms
Keywords
  • Route finding under uncertainty
  • Edge-disjoint paths
  • Optimization
  • Exact algorithms
  • Approximation algorithms
  • Vectorization

Metrics

Abstract

Motivated by challenges occurring in disaster relief operations, we study the problem to find two edge-disjoint paths in a graph whose arcs are labeled with traversability probabilities that maximize the probability that (at least) one of the paths is traversable.
We show that this problem is NP-hard. To solve the problem, we propose to model it as a bi-objective problem, taking traversability probabilities of the two individual paths as objective functions. We show that an optimal solution to our problem is an extreme-supported solution of the so defined bi-objective problem and exploit this property to find optimal solutions. Furthermore, we present two approximation approaches, and compare the approaches experimentally with respect to runtime and solution quality.

Cite As Get BibTex

Aaron Neugebauer and Marie Schmidt. Finding Maximum-Success Disjoint Paths. In 26th Symposium on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2026). Open Access Series in Informatics (OASIcs), Volume 147, pp. 8:1-8:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026) https://doi.org/10.4230/OASIcs.ATMOS.2026.8

Author Details

Aaron Neugebauer
  • Department of Computer Science, University of Würzburg, Germany
  • Image Processing Department, Fraunhofer ITWM-Institute for Industrial Mathematics, Kaiserslautern, Germany
Marie Schmidt
  • Department of Computer Science, University of Würzburg, Germany

Supplementary Materials

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