Guided Local Search

Guided Local Search is a metaheuristic optimization framework that extends local search algorithms by systematically penalizing entrenched suboptimal solution features to escape local optima and guide the search toward higher-quality regions of the solution space.

197

Publications

14K

Citations

541

Authors

300

Institutions

Publications per year

2017–2026

80

Variants

Gls

Authors

541

  1. DV
    Dirk Van Oudheusden

    KU Leuven, Belgium

    5 publications · 666 citations

    5

    h-index

  2. TS
    Thomas Stützle

    Université Libre de Bruxelles, Belgium

    3 publications · 114 citations

    3

    h-index

  3. DC
    Dirk Cattrysse

    KU Leuven, Belgium

    3 publications · 250 citations

    3

    h-index

  4. SM
    Seyedali Mirjalili

    Torrens University Australia, Australia

    3 publications · 612 citations

    3

    h-index

  5. ET
    Edward Tsang

    University of Essex, United Kingdom

    3 publications · 561 citations

    3

    h-index

1–5 of 541

Venues

  1. European Journal of Operational Research

    13 publications · 1.4K citations

    12

    h-index

  2. Applied Soft Computing

    9 publications · 491 citations

    9

    h-index

  3. Expert Systems with Applications

    8 publications · 320 citations

    8

    h-index

  4. Knowledge-Based Systems

    8 publications · 1.3K citations

    8

    h-index

  5. Computers & Operations Research

    6 publications · 212 citations

    6

    h-index

1–5