Joint Optimization

Joint Optimization is an academic method that integrates multiple interdependent components or objectives into a unified framework to simultaneously optimize their performance, thereby distinguishing itself from sequential or isolated optimization approaches by leveraging synergies across coupled subproblems.

3.3K

Publications

171K

Citations

8.9K

Authors

1.7K

Institutions

Publications per year

2017–2026

2.2K

Authors

8.9K

  1. FR
    F. Richard Yu

    Carleton University, Canada

    36 publications · 3.6K citations

    30

    h-index

  2. ZH
    Zhu Han

    University of Houston, United States

    28 publications · 2K citations

    21

    h-index

  3. VC
    Victor C. M. Leung

    University of British Columbia, Canada

    21 publications · 1.8K citations

    19

    h-index

  4. DN
    Dusit Niyato

    Nanyang Technological University, Singapore

    19 publications · 1.3K citations

    19

    h-index

  5. TQ
    Tony Q. S. Quek

    Singapore University of Technology and Design, Singapore

    19 publications · 1K citations

    17

    h-index

1–5 of 8.9K

Venues

  1. IEEE Transactions on Wireless Communications

    152 publications · 10.5K citations

    58

    h-index

  2. IEEE Transactions on Vehicular Technology

    172 publications · 10.3K citations

    52

    h-index

  3. IEEE Internet of Things Journal

    108 publications · 7.7K citations

    51

    h-index

  4. IEEE Transactions on Communications

    110 publications · 6.3K citations

    47

    h-index

  5. IEEE Access

    104 publications · 4.6K citations

    39

    h-index

1–5