Routing Simulator (Environment Model)
• Dynamic requests
• Travel/energy/time updates
State Representation + SAP
• Encode customers/depots/EVs
• Mask infeasible actions
Multi-Head Attention (MHA) Encoder
• Contextual dependencies
• Attention-based embedding
MARL — DDQN + PER (CLDE)
• Centralized learning
• Decentralized execution
Double-Adaptive VNS (DA-VNS)
• Adaptive shaking
• Adaptive VND refinement
Outputs / Results
• Optimized routes
• Distance / service rate
• Time-window feasibility
• Explanations
Explainable AI (XAI) Layer
• Attention viz (MHA)
• SHAP/LIME feature importance
• Operator contribution (DA-VNS)
by hh