Unconstrained Optimization

Unconstrained Optimization is a branch of mathematical optimization that studies the minimization or maximization of an objective function over a domain of decision variables without any explicit constraints restricting those variables.

1.3K

Publications

114.7K

Citations

2K

Authors

874

Institutions

Publications per year

2017–2026

315

Authors

2K

  1. PL
    Philippe L. Toint

    University of Namur, Belgium

    32 publications · 3.5K citations

    26

    h-index

  2. NA
    Neculai Andrei

    National Institute for Research and Development in Informatics - ICI Bucharest, Romania

    31 publications · 2.1K citations

    25

    h-index

  3. SL
    Stefano Lucidi

    Sapienza University of Rome, Italy

    17 publications · 1K citations

    16

    h-index

  4. NI
    Nicholas I. M. Gould

    Rutherford Appleton Laboratory, United Kingdom

    15 publications · 2K citations

    15

    h-index

  5. CC
    Coralia Cartis

    University of Oxford, United Kingdom

    15 publications · 1.5K citations

    15

    h-index

1–5 of 2K

Venues

  1. SIAM Journal on Optimization

    87 publications · 21.1K citations

    49

    h-index

  2. Journal of Optimization Theory and Applications

    56 publications · 3.5K citations

    30

    h-index

  3. Mathematical Programming

    41 publications · 5K citations

    29

    h-index

  4. Optimization methods & software

    64 publications · 2.2K citations

    26

    h-index

  5. Journal of Computational and Applied Mathematics

    38 publications · 1.5K citations

    25

    h-index

1–5