Repetitive project rescheduling study considering crew size
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
During the execution of repetitive projects, various uncertainties are often encountered, leading to delays and cost overruns, and effective rescheduling strategies can address these risks. Firstly, the study discusses the rationality and limitations of the “natural rhythm” principle of Line of Balance scheduling in theory and practice and proposes a comprehensive rescheduling strategy that simultaneously changes the size and number of crews, breaking the limitation of the “natural rhythm” on the size of crews. A rescheduling optimization model is constructed on this basis and solved using an exact algorithm. Then, a highway project is taken as an example for calculation analysis. The results show that the comprehensive rescheduling strategy has significant cost advantages in projects of different sizes. This study provides new solution ideas for the repetitive project rescheduling problem to cope with uncertainty disturbances in a more economical way.
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 | 0.005 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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