Optimization for Multiple Constraints Transportation Path Based on Mutated Ant Colony Algorithm
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Bibliographic record
Abstract
To solve the problem that there are multiple constraints limited in optimizing transportation path,a mathematical model of multiple constraints transportation path optimization problem(MCTPOP) was established.Based on general ant colony algorithm,a mutation mechanism is introduced into this algorithm which adopts the mode of mutation probability increasing linearly.According to the characteristics of mutated ants searching path,a pheromone updating policy called Ant-encocontr is provided in this paper.In order to solve MCTPOP with mutated ant colony algorithm,we design a simulate experiment.Simulation results demonstrated that the algorithm can reduce the possibility of falling in local optimum and improve the search ability of general ant colony algorithm.It's an effective algorithm for solving MCTPOP.
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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 | 0.001 | 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