A decision framework for location-allocation problems: A case study in tea industry
Why this work is in the frame
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Bibliographic record
Abstract
This paper propose the use of the Fuzzy Analytical Hierarchy process (FAHP) and Goal Programming (GP) as an aid in making location-allocation decision and suggest a systematic method for the site selection and product allocation problem. The method can be seen as a decision support framework, which links various objectives, subjective and critical factors in the location-allocation problem to make an optimal decision in which fits best for both operations managers and investors. Important advantages of applying the framework are (1) the ability to decompose the complex problem in smaller problems, (2) the possibility of an efficient and effective contribution of operations managers and investors in decision making process, (3) the detail assessment of the selected location alternative. A demonstration of the application of this methodology in tea industry in Iran is presented.
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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 | 0.000 | 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