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PreprintCC BY 4.0arXiv

The Stochastic Team Orienteering Problem

  • Alberto Guastalla
  • Jean-François Côté
  • Roberto Aringhieri
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Abstract

This paper analyses the Stochastic Team Orienteering Problem (STOP), a stochastic variant of the Team Orienteering Problem (TOP). In the STOP, travel times are represented by random variables. The objective is to determine a set of routes that maximises the expected collected profit. We model the problem as a two-stage stochastic integer program and propose an exact solution method based on the Integer L-shaped method. We also consider a set of non-linear chance constraints to restrict the search to highly reliable routes. In the first-stage, a set of routes is selected, while in the second-stage the recourse evaluates the expected profit of the selected routes. We present a new set of optimality cuts and strengthen the formulation by considering valid inequalities and constraints liftings. Computational results provide a comprehensive analysis of the algorithm using the standard TOP benchmark dataset from the literature.

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Cite

BibTeXRIS
BibTeX
@misc{guastalla2026stochastic,
  title = {{The Stochastic Team Orienteering Problem}},
  author = {Alberto Guastalla and Jean-François Côté and Roberto Aringhieri},
  howpublished = {arXiv},
  year = {2026},
  month = sep,
  doi = {10.48550/arxiv.2608.29119},
  eprint = {2608.29119},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2608.29119},
  note = {CC BY 4.0},
}
RIS
TY  - UNPB
TI  - The Stochastic Team Orienteering Problem
AU  - Alberto Guastalla
AU  - Jean-François Côté
AU  - Roberto Aringhieri
PY  - 2026
DA  - 2026/09/09
PB  - arXiv
DO  - 10.48550/arxiv.2608.29119
UR  - https://arxiv.org/abs/2608.29119
AB  - This paper analyses the Stochastic Team Orienteering Problem (STOP), a stochastic variant of the Team Orienteering Problem (TOP). In the STOP, travel times are represented by random variables. The objective is to determine a set of routes that maximises the expected collected profit. We model the problem as a two-stage stochastic integer program and propose an exact solution method based on the Integer L-shaped method. We also consider a set of non-linear chance constraints to restrict the search to highly reliable routes. In the first-stage, a set of routes is selected, while in the second-stage the recourse evaluates the expected profit of the selected routes. We present a new set of optimality cuts and strengthen the formulation by considering valid inequalities and constraints liftings. Computational results provide a comprehensive analysis of the algorithm using the standard TOP benchmark dataset from the literature.
ER  -