Profit maximization in reverse logistics based on disassembly scheduling using hybrid bee colony and bat optimization
Why this work is in the frame
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Bibliographic record
Abstract
This work was undertaken to develop a strategy to enhance the profit in the reverse logistics of end-of-life products. In this paper, a novel strategy based on hybrid bee colony and bat optimization technique is presented to perform reverse logistics. The aim of the present paper is to maximize the profit in reverse logistic based manufacturing. The proposed optimization technique was used to schedule the disassembly of end-of-life products so that the time spent in reverse logistics was reduced. Moreover, the proposed technique increases the amount of product required during disassembly, so that the loss of component is reduced. Thus, the proposed technique can enhance the manufacturer’s profit by reducing the time and cost required for disassembly. Ultimately, the proposed technique can provide a suitable technique for multi-period disassembly in manufacturing industries.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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