Grade-tonnage Optimization

Grade-Tonnage Optimization is a computational modeling framework in mining engineering that determines the optimal trade-off between ore grade and mineable tonnage by selectively identifying which blocks of a mineral deposit to extract in order to maximize economic value under geological uncertainty.

11

Publications

358

Citations

17

Authors

7

Institutions

Publications per year

2017–2026

1

Authors

17

  1. YH
    Yong He

    Guangdong University of Technology, China

    2 publications · 26 citations

    2

    h-index

  2. NL
    Nuo Liao

    Guangdong University of Technology, China

    2 publications · 26 citations

    2

    h-index

  3. MO
    Morteza Osanloo

    Amirkabir University of Technology, Iran

    2 publications · 49 citations

    2

    h-index

  4. RD
    Roussos Dimitrakopoulos

    McGill University, Canada

    2 publications · 198 citations

    2

    h-index

  5. MJ
    Mohsen Jamshidi

    Amirkabir University of Technology, Iran

    1 publications · 10 citations

    1

    h-index

1–5 of 17

Venues

  1. 1

    h-index

  2. Neural Computing and Applications

    1 publications · 14 citations

    1

    h-index

  3. Soft Computing

    1 publications · 12 citations

    1

    h-index

  4. 1

    h-index

  5. 1

    h-index

1–5