Towards Sustainable Facility Location – A Literature Review
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
Facility location methods play a crucial role in specifying the optimum location options for various types of facilities. A question that arises is what makes a facility location decision a sustainable one? Facility location, also known as location analysis, is a known concept in the literature, but sustainable facility location is not. This requires appropriately defining the concept and framing the problem in order to address the relevant issues. Facility location models in the existing literature do not effectively include all the requirements of sustainable development. This paper serves as a discussion of the current literature concerning the sustainability aspects of the location problem. The aim is to conduct a comprehensive literature review to identify the characteristics of the sustainable facility location problem and propose a framework for classification of sustainability characteristics. The study shows that the location literature has steadily progressed toward considering not only economic but also social and environmental criteria in location decisions; but that many steps remain to be taken toward developing location models that integrate all three aspects of sustainability into decision making. The main motivation for the current study is to provide a foundation from which issues of sustainable development can be built into facility location and siting models.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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