Search Space Reduction

Search Space Reduction is a methodological strategy in computational optimization and bioinformatics that systematically diminishes the set of feasible solutions explored during search processes by eliminating regions provably devoid of optimal solutions, thereby enhancing computational efficiency without compromising solution optimality.

744

Publications

38.9K

Citations

2.4K

Authors

884

Institutions

Publications per year

2017–2026

326

Authors

2.4K

  1. ZD
    Zuomin Dong

    University of Victoria, Canada

    5 publications · 263 citations

    5

    h-index

  2. AX
    Alex X. Liu

    Michigan State University, United States

    5 publications · 289 citations

    5

    h-index

  3. BX
    Bing Xue

    Victoria University of Wellington, New Zealand

    4 publications · 2K citations

    4

    h-index

  4. HD
    Haipeng Dai

    Nanjing University, China

    4 publications · 256 citations

    4

    h-index

  5. WM
    Wojciech Matusik

    Massachusetts Institute of Technology, United States

    4 publications · 331 citations

    4

    h-index

1–5 of 2.4K

Venues

  1. arXiv (Cornell University)

    Repository · 32 publications · 718 citations

    17

    h-index

  2. IEEE Access

    16 publications · 633 citations

    13

    h-index

  3. Applied Soft Computing

    10 publications · 665 citations

    10

    h-index

  4. IEEE Transactions on Evolutionary Computation

    9 publications · 2.3K citations

    9

    h-index

  5. IEEE Transactions on Power Systems

    9 publications · 1.6K citations

    8

    h-index

1–5