{"id":26583166,"url":"https://github.com/naveen88112/vehicle-routing-problem","last_synced_at":"2026-04-13T21:31:31.942Z","repository":{"id":271696559,"uuid":"914288541","full_name":"Naveen88112/Vehicle-Routing-Problem","owner":"Naveen88112","description":"Vehicle Routing Problem (VRP) Solver This project applies a Genetic Algorithm (GA) to optimize the Vehicle Routing Problem (VRP). 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The goal is to optimize delivery routes for multiple vehicles, reducing travel distance and enhancing efficiency.\n\nFeatures\n- Problem Representation: Models VRP with multiple delivery locations and vehicles.\n- Genetic Algorithm Implementation: Uses DEAP for evolutionary computation.\n- Fitness Evaluation: Optimizes routes based on total travel distance.\n- Mutation \u0026 Crossover: Ensures diversity in route solutions.\n- Visualization: Displays optimized routes using Matplotlib.\n\nTechnologies Used\n- Python\n- DEAP (Distributed Evolutionary Algorithms in Python)\n- NumPy\n- Matplotlib\n\nHow to Run\n1. Clone the repository:\n   \n   \"git clone https://github.com/yourusername/vrp-solver.git\"\n   \n2. Install dependencies:\n   \n   \"pip install matplotlib deap numpy\"\n   \n3. Run the Jupyter Notebook or execute the script:\n   \n   \"python vrp_solver.py\"\n\nResults \u0026 Insights\n- The genetic algorithm optimizes routes for efficient deliveries.\n- Crossover and mutation improve route diversity and effectiveness.\n- Visualization provides insights into route optimization strategies.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fnaveen88112%2Fvehicle-routing-problem","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fnaveen88112%2Fvehicle-routing-problem","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fnaveen88112%2Fvehicle-routing-problem/lists"}