Sustainable Transportation Planning for Djebel Onk's Open-Pit Phosphate Mine in Algeria: Using Queuing Theory and Cost-Emission Analysis
Bibliographic record
Abstract
Efficient mineral transportation is critical for sustainable open-cast mining operations.Queuing theory offers a practical approach to optimizing truck-shovel systems and address truck waiting times at loading and unloading sites.This research evaluates the excavator-truck system at an Algerian open-pit phosphate mine using an M/M/1 queuing model.The model reveals relationships between truck fleet size and queue length, waiting time, shovel utilization, and overall production.Moreover, loading and transportation costs are analysed to determine the optimal truck fleet size that minimizes costs and emissions.The match factor further evaluates fleet compatibility for sustainable planning.This systems analysis provides insights into achieving efficient, low-emission truck-shovel operations through optimized fleet sizes, reduced waiting times, and cost-emission optimization.The integrated queuing model and planning techniques presented can guide sustainable planning of open-pit mining transportation systems.Focusing on efficiency, costs, and emissions allows strategic optimization for both economic and environmental sustainability.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".