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Python implementation solving complex problems with genetic algorithms, optimizing polynomial curve fitting and the knapsack problem efficiently.

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Genetic Algorithms

Brief

This repository provides Python implementations of genetic algorithms for solving two distinct problems: curve fitting and the knapsack problem. Genetic algorithms are employed to find optimal solutions in both scenarios.

The knapsack problem solver employs a genetic algorithm to maximize the total value of selected items placed in a knapsack, considering the weight capacity of the knapsack.

The curve fitting algorithm aims to find the best coefficients for a polynomial equation, minimizing the distance between the curve and a given set of data points.

Installation

To use the algorithms in this repository, you will need Python 3 installed on your system. You can download Python 3 from the official website: Python Downloads

Once you have Python 3 installed, you can run the programs for curve fitting and the knapsack problem.

Contributing

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

Please make sure to update tests as appropriate.

Author

👤 Michael Maher

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📝 License

Copyright © 2023 Michael Maher.
This project is MIT licensed.

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Python implementation solving complex problems with genetic algorithms, optimizing polynomial curve fitting and the knapsack problem efficiently.

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