Problem Hardness

Problem Hardness is a quantitative measure within fitness landscape analysis that characterizes the inherent difficulty of solving an optimization problem based on the structure and distribution of local optima, modality, and navigability of the search space.

224

Publications

14.6K

Citations

480

Authors

256

Institutions

Publications per year

2017–2026

36

Variants

Problem Difficulty

Authors

480

  1. RP
    Riccardo Poli

    University of Essex, United Kingdom

    6 publications · 260 citations

    6

    h-index

  2. XY
    Xin Yao

    University of Birmingham, United Kingdom

    5 publications · 307 citations

    5

    h-index

  3. AP
    Adam Prügel‐Bennett

    University of Southampton, United Kingdom

    4 publications · 114 citations

    4

    h-index

  4. TW
    Toby Walsh

    Data61, Australia

    4 publications · 340 citations

    4

    h-index

  5. JS
    John Slaney

    Australian National University, Australia

    3 publications · 212 citations

    3

    h-index

1–5 of 480

Venues

  1. IEEE Transactions on Evolutionary Computation

    10 publications · 1.1K citations

    10

    h-index

  2. arXiv (Cornell University)

    Repository · 8 publications · 261 citations

    8

    h-index

  3. Evolutionary Computation

    7 publications · 481 citations

    7

    h-index

  4. Theoretical Computer Science

    5 publications · 765 citations

    5

    h-index

  5. European Journal of Operational Research

    4 publications · 106 citations

    4

    h-index

1–5