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  This project implements a deep reinforcement learning framework to solve the Vehicle Routing Problem with Time Windows (VRPTW) using Transformer-based models. It also integrates Google OR-Tools as a classical baseline for comparison.
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  πŸ“ Project Structure
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  bash
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  Copy
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  An actor-critic reinforcement learning strategy with a learnable baseline
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- Beam Search and Greedy decoding options
 
 
 
 
 
 
 
 
 
 
 
 
 
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  This project implements a deep reinforcement learning framework to solve the Vehicle Routing Problem with Time Windows (VRPTW) using Transformer-based models. It also integrates Google OR-Tools as a classical baseline for comparison.
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  πŸ“ Project Structure
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  bash
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  Copy
 
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  An actor-critic reinforcement learning strategy with a learnable baseline
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+ Beam Search and Greedy decoding options
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+
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+ πŸ’Ύ Data Persistence
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+ This Space writes logs, model checkpoints, and training history to the `/data` directory.
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+
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+ Make sure your `run.py` and `inference.py` use `/data/` for saving/loading models and results.
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+ Example:
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+ ```python
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+ with open("/data/train_results.txt", "a") as f:
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+ f.write(...)
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+ torch.save(model.state_dict(), "/data/model_state_dict.pt")