Bibliographic record
Abstract
This paper focuses on the optimal operation of water supply networks. We model water supply networks using hydraulic constraints and formulate a joint optimal pump scheduling and water flow problem (OWF) using the hydraulic characteristics of variable speed pumps. OWF is a mixed-integer nonlinear program. This problem is nonconvex, and hence NP-hard. To compute an exact solution of OWF, we first focus on the feasibility region of OWF and propose a mixed-integer second-order cone relaxation for the feasibility region of OWF. We prove that the proposed relaxation is exact for several relevant network topologies. We then focus on the objective function in OWF and show that for some energy metrics, OWF can be transformed into a mixed-integer second-order cone program. Furthermore, we propose an ADMM-based algorithm to compute suboptimal solutions to OWF and lower bounds on the optimal value of the objective in OWF when the objective function is nonconvex. Finally, we consider a real-world water network, and demonstrate the effectiveness of the proposed relaxation in computing the optimal pump schedules and water flows.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".