Towards a deterministic sustainable cost-effective water supply chain
Bibliographic record
Abstract
Managing water resources is one of the most challenging problems in today’s world. There is an immense change in climate change, population growth, and environment, thereby increasing pressures on water resources. Due to future uncertainty and availability of resources, many priorities should be taken into account in the drinking-water system such as environmental impacts, distribution costs and fixed costs. This paper proposes a deterministic mixed-integer linear programming (MILP) model for planning and designing a water supply chain network in order to optimize multi-objective problems. The model considers costs which include fixed and variable costs, in addition, it considers sustainability in terms of environmental viewpoint. The applicability of the model is appraised through a case study whose data gathered from related articles and water and waste company reports in Iran, which consists of five candidate reservoir nodes and four dam nodes besides eleven candidate locations for treatment plants. Thereafter, the proposed model has been coded in GAMS® optimization software. The model could be an expedient tool in order to manage urban water supply chains in a cost-effective and sustainable manner to satisfy water demand at every time period.
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How this classification was reachedexpand
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 | 0.001 |
| 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) | 0.001 | 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 teacher head, 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".