Balancing Sustainability and Decision Maker Preferences in Regional Development Location Selection: A Multi-criteria Approach Using AHP and Fuzzy Goal Programming
Bibliographic record
Abstract
In this study, we address the challenge of balancing sustainability and decision-maker preferences in regional development location selections.We propose a multi-criteria decision-making framework combining the Analytical Hierarchy Process (AHP) and Fuzzy Goal Programming (FGP) to evaluate potential sites.AHP is utilized to prioritize criteria, incorporating both quantitative and qualitative factors, while FGP allows for the accommodation of uncertainty and conflicting goals.Our findings reveal that this integrated approach provides a robust, systematic method for identifying optimal locations that align with both sustainability goals and stakeholder priorities.The analysis revealed the following satisfaction levels: Price 61.11%, Quality 80.4%, Delivery Time 79.3%, Carbon Emission 91.76%, and Preference 51.18%.The findings emphasize the complex process of selecting vendors within the palm oil supply chain.The implications of this research suggest enhanced decision-making efficiency and effectiveness in regional planning, promoting sustainable development practices.
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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 | 0.014 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".