Research Article
[Retracted] Large-Scale Scheduling Model Based on Improved Ant Colony Algorithm
Table 1
Model parameters (
represents XGBoost;
represents ant colony algorithm).
| Parameter name | Value | Meaning |
| Max_depth1 | 5 | Maximum number of iteration layers | Learning_rate1 | 0.1 | Learning rate | n_estimators1 | 40 | Maximum number of iterations | ALPHA2 | 2 | Pheromone importance factor | BETA2 | 1 | Heuristic function importance factor | RHO2 | 0.6 | Pheromone volatility factor | Q2 | 200 | Number of iterations | T2 | 200 | Initial carrying capacity | State2 | 15 | Maximum number of stations |
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