Coordinating order acceptance and integrated lot streaming-batch delivery scheduling considering third party logistics
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
Inspired by the industries such as food and beverage, metal and steel, as well as petroleum and petrochemical ones, the current study addresses a joint order acceptance and scheduling, lot streaming in a flexible flow shop and batch delivery problem. For maximizing a profit objective function with trading off between the revenue of the accepted orders and the costs incurred, a novel mixed integer linear programming is proposed. This paper develops a hybrid metaheuristic algorithm based on the Genetic Algorithm. In the developed algorithm, (1) a heuristic, (2) a local search, and (3) a restart phase is proposed. To set the appropriate parameters of the algorithms, Taguchi experimental design was applied. The obtained results reveal the appropriate performance of the hybrid genetic algorithm.
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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