A review of methods, techniques and tools for project planning and control
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 purpose of this article is to provide a brief review of methods and techniques developed for the most commonly studied decision-making problems in project planning and control over the last decade. These problems involve project representation, project scheduling, resource allocation, risk analysis, time and cost performance evaluation, time, cost, and cash flow forecasting, optimal timing of control points, and corrective action decision-making. We also review recent tools developed for project planning and control. The emphasis is on recent contributions, but several older yet important works are also cited. Our analysis shows an increasing attention to the stochastic nature of projects in planning and control decision and processes. Recent attention has also been put at improvements in existing project control techniques as well as developing new methods to automate data collection, process, and generate more integrated project plan. More importantly, our review highlights an important shift in the project planning and control research field, which has been largely dominated by the project scheduling literature in the past, as short term and reactive decision-making bring new challenges and opportunities to project organisations and researchers.
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 | 0.059 | 0.085 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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