A Goal Programming Model for Dispatching Trucks in an Underground Gold Mine
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The cost of transporting mined material in an underground mine is major. This cost typically represents between 50 to 60 percent of a mine’s total operating costs. The problem of dispatching trucks in an underground gold mine is, therefore, of major economic importance and warrants the use of a decision support model. The developments of a realistic decision-support model for the dispatching problem in an underground gold mine is addressed in this paper. The problem must address multiple conflicting objectives and therefore a goal programming model was formulated. The model was applied to a case study, the Red Lake underground gold mine, in Ontario, Canada. The results showed major improvements in meeting the multiple objectives of this problem versus a single objective model. The results illustrate the flexibility that the dispatching problem (in underground gold mines) yields when solved for multiple objectives using a goal programming model.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it