-Service-Facility-allocation-to-locations-using-Genetic-Algorithm

Using Genetic Algorithms to optimize the allocation of services or facilities to specific locations. The primary application of this project is in the context of Covid-19 vaccine center locations, aiming to strategically position vaccination facilities for efficient and widespread coverage.

Key Features:

• Genetic Algorithm Implementation: The core of the project is built around a Genetic Algorithm, a heuristic search and optimization technique inspired by natural selection. The algorithm evolves a population of potential solutions over generations, mimicking the process of natural selection to find an optimal solution.
• Spatial Optimization: The project considers geographical and demographic factors to optimize the allocation of service or facility centers. This is particularly relevant for Covid-19 vaccine distribution, where factors like population density, transportation networks, and healthcare infrastructure play a crucial role.
• Scalability: The solution is designed to scale, accommodating varying sizes of regions and populations. This makes it adaptable for different scenarios, from local municipalities to entire regions or countries.

Run the Algorithm:

Execute the Genetic Algorithm to find the optimized allocation of service or facility centers.

Visualization:

. Visualize the results through interactive reports, facilitating decision-making and strategic planning.

Dependencies:

1. Python (>= 3.6)
2. NumPy
3. Matplotlib
4. math
5. random