English

Finding Risk-Averse Shortest Path with Time-dependent Stochastic Costs

Artificial Intelligence 2017-01-04 v1

Abstract

In this paper, we tackle the problem of risk-averse route planning in a transportation network with time-dependent and stochastic costs. To solve this problem, we propose an adaptation of the A* algorithm that accommodates any risk measure or decision criterion that is monotonic with first-order stochastic dominance. We also present a case study of our algorithm on the Manhattan, NYC, transportation network.

Keywords

Cite

@article{arxiv.1701.00642,
  title  = {Finding Risk-Averse Shortest Path with Time-dependent Stochastic Costs},
  author = {Dajian Li and Paul Weng and Orkun Karabasoglu},
  journal= {arXiv preprint arXiv:1701.00642},
  year   = {2017}
}

Comments

accepted at MIWAI 2017

R2 v1 2026-06-22T17:39:51.937Z