Jkakai001/Bus-Route-Optimization

Network Theory-Based Optimization of Urban Bus Systems: A Multi-Modal Competition Analysis of Kigali City, Rwanda # Bus Network Optimization System A comprehensive system for analyzing and optimizing bus networks with multi-modal competition analysis. ## Project Structure ``` optimization_code/ ├── main.py # Main execution file ├── scripts/ # All analysis modules │ ├── __init__.py │ ├── data_loader.py # Load and process datasets │ ├── network_builder.py # Build network graph │ ├── stop_analyzer.py # Analyze stop performance │ ├── competition_analyzer.py # Analyze mode competition │ ├── optimizer.py # Generate optimization recommendations │ ├── visualizer.py # Create visualizations │ └── report_generator.py # Generate reports ├── data/ # All input datasets │ ├── bus_stops/ # Bus stops shapefile │ ├── roads/ # Road network shapefile │ ├── bus_od_matrix.csv # Bus OD matrix │ ├── moto_cab_mar_2022_OD_table.csv │ └── moto_cab_april_2022_OD_table.csv └── results/ # All output files ├── *.png # Visualization files └── *.csv # Analysis results ``` ## Module Descriptions ### 1. data_loader.py **Purpose**: Load and preprocess all transportation datasets. **What it does**: - Loads bus stops spatial data (shapefile) - Loads road network spatial data (shapefile) - Loads bus Origin-Destination (OD) matrix - Loads motorcycle and car taxi OD tables - Maps coordinate-based trips to nearest bus stops - Creates combined demand matrices with conversion factors - Validates and enhances data **Expected Results**: Processed datasets ready for analysis ### 2. network_builder.py **Purpose**: Create demand-weighted network graph from bus stops and infrastructure. **What it does**: - Creates NetworkX graph with bus stops as nodes - Connects stops based on spatial proximity - Weights edges by travel time, demand, and competition factors - Adds comprehensive demand attributes to nodes **Expected Results**: Network graph representing the …