Optimizing Earthmoving Job Planning Based on Evaluation of Temporary Haul Road Networks Design for Mass Earthworks Projects
Why this work is in the frame
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Bibliographic record
Abstract
As a critical component of planning mass earthworks projects, designing effective haul road networks is conducive to delivering the project on time and under budget. The research reported in this paper proposes a grid-based temporary road network design method applicable to a site for which grading design has been completed. Further adding to the existing body of knowledge, a quantitative methodology is proposed for optimizing the detailed planning of earthmoving jobs based on a particular temporary haul road network design. Each job is defined in terms of the source cell, the destination cell, the earth volume, and the shortest-hauling-time path between source and destination. Through seamless integration of the Floyd-Warshall algorithm and linear programming model, the shortest average haul time for a truckload can be obtained while automatically fulfilling site grading design specifications. Based on the resulting average haul time, cost equations are defined to account for (1) the direct truck-hauling crew cost; and (2) building, maintenance, and removal costs of temporary haul roads. As such, the cost associated with executing the optimized earthmoving job plan over a particular haul road network design can be readily assessed, making it straightforward for project managers to compare alternatives. The proposed methodology is demonstrated in steps using a numerical example and further applied in a case study based on a real-world project in northern Alberta.
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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 | 0.001 | 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 | 0.000 | 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