Research Article
The Path Optimization Algorithm of Car Navigation System considering Node Attributes under Time-Invariant Network
| | Algorithm | Parameters | Value |
| | ACO | Ant number m | 80 | | Heuristic factor a | 1 | | Pheromone volatility ρ | 0.3 |
| | GA | Population size M | 100 | | Cross probability P1 | 0.6 | | Mutation probability p2 | 0.01 |
| | NNA | Network layers | 3 | | Number of input nodes | 6 | | Number of output nodes | 1 | | Number of hidden layer nodes | 12 |
| | PSO | Particle swarm size | 80 | | Learning factor c1 | 1.5 | | Learning factor c2 | 2.0 | | Inertia weight parameter | 0.9 |
| | OPABRL | Learning factor | 0.7 | | Discount factor | 1 | | Greedy strategy | 0.5 |
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