Optimization-aware Generation

Optimization-Aware Generation is a computational synthesis methodology that integrates optimization objectives and constraints directly into the generative process to ensure that generated artifacts are inherently aligned with performance, efficiency, or quality criteria defined by the optimization framework.

12

Publications

742

Citations

39

Authors

20

Institutions

Publications per year

2017–2026

8

Authors

39

  1. AK
    Amin Khodaei

    University of Denver, United States

    1 publications · 45 citations

    1

    h-index

  2. LX
    Lei Xi

    China Three Gorges University, China

    1 publications · 41 citations

    1

    h-index

  3. JK
    Jože Korelc

    University of Ljubljana, Slovenia

    1 publications · 121 citations

    1

    h-index

  4. ML
    Matthijs Langelaar

    Delft University of Technology, Netherlands

    1 publications · 43 citations

    1

    h-index

  5. WL
    Wei‐keng Liao

    Northwestern University, United States

    1 publications · 48 citations

    1

    h-index

1–5 of 39

Venues

  1. Communications of the ACM

    1 publications · 226 citations

    1

    h-index

  2. Theoretical Computer Science

    1 publications · 121 citations

    1

    h-index

  3. CSEE Journal of Power and Energy Systems

    1 publications · 41 citations

    1

    h-index

  4. Mathematical Programming Computation

    1 publications · 14 citations

    1

    h-index

  5. Computers & Structures

    1 publications · 43 citations

    1

    h-index

1–5