Probabilistic Shortest Paths

Probabilistic Shortest Paths is a shortest path framework that models edge weights or path existence as random variables, incorporating uncertainty into the computation of shortest paths through probabilistic analysis.

45

Publications

2.5K

Citations

117

Authors

69

Institutions

Publications per year

2017–2026

13

Authors

117

  1. WH
    William H. K. Lam

    Hong Kong Polytechnic University, Hong Kong SAR China

    3 publications · 231 citations

    3

    h-index

  2. PB
    Pitu B. Mirchandani

    University of Arizona, United States

    3 publications · 334 citations

    3

    h-index

  3. ST
    Sylvie Thiébaux

    Australian National University, Australia

    2 publications · 57 citations

    2

    h-index

  4. RT
    Rui Tong

    Beihang University, China

    2 publications · 87 citations

    2

    h-index

  5. FT
    Felipe Trevizan

    Australian National University, Australia

    2 publications · 57 citations

    2

    h-index

1–5 of 117

Venues

  1. Networks

    3 publications · 165 citations

    3

    h-index

  2. Computers & Operations Research

    3 publications · 249 citations

    3

    h-index

  3. Transportation Research Part B Methodological

    3 publications · 398 citations

    3

    h-index

  4. Expert Systems with Applications

    2 publications · 87 citations

    2

    h-index

  5. 2

    h-index

1–5