Production and Inventory Model Using Net Present Value
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
Using the net present value is the standard methodology in theoretical analysis, and the most frequently used method for making financial decisions. However, net present value is rarely used in production and inventory decisions. The main reasons appear to be the complexity of the formulae and the robustness of the EOQ model. We investigate the general multiproduct, multistage production and inventory model using the net present value of its total cost as the objective function. A power-of-two heuristic gives us a near optimal solution to this problem. If the base period is fixed (or varied), the solution based on the best power-of-two heuristic will be within 6.2% (or 2.1% ) of the optimal. This result is surprisingly similar to models using the long-term average cost. The average cost does not reflect the time value of money. Does this mean that decisions based on average cost are significantly inferior to those based on net present value? The answer is quite surprising. If we include discounted production cost in the holding cost, it turns out that the decision based on average cost is only 9.6% (in terms of the net present value of the total cost) worse than the decision based on the net present value. However, the reorder interval based on the average cost could be much longer than that derived using net present value. This result shows that average cost is a good approximation to the net present value when the demands are deterministic.
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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 it