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https://github.com/muhammadsaadhsn/sudokusolver-magicsquarepuzzlesolver
This repository includes a Sudoku solver and a Magic Square puzzle solver. The Sudoku solver employs backtracking search with heuristics and the AC-3 algorithm. The Magic Square solver uses a genetic algorithm to solve 3x3 puzzles. Both solvers are implemented in Python with efficient and optimized approaches.
https://github.com/muhammadsaadhsn/sudokusolver-magicsquarepuzzlesolver
ac-3 magicsquare sudoku-solver
Last synced: 5 days ago
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This repository includes a Sudoku solver and a Magic Square puzzle solver. The Sudoku solver employs backtracking search with heuristics and the AC-3 algorithm. The Magic Square solver uses a genetic algorithm to solve 3x3 puzzles. Both solvers are implemented in Python with efficient and optimized approaches.
- Host: GitHub
- URL: https://github.com/muhammadsaadhsn/sudokusolver-magicsquarepuzzlesolver
- Owner: muhammadsaadhsn
- License: mit
- Created: 2024-06-28T06:48:31.000Z (8 months ago)
- Default Branch: main
- Last Pushed: 2024-06-28T06:53:30.000Z (8 months ago)
- Last Synced: 2025-01-28T15:39:50.936Z (17 days ago)
- Topics: ac-3, magicsquare, sudoku-solver
- Language: Jupyter Notebook
- Homepage:
- Size: 7.81 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Sudoku Solver and Magic Square Puzzle Solver
## Overview
This repository contains two projects: a Sudoku solver and a Magic Square puzzle solver. The Sudoku solver uses backtracking search with various heuristics and the AC-3 algorithm for arc consistency. The Magic Square puzzle solver uses a genetic algorithm to find solutions to a 3x3 magic square puzzle.
## Sudoku Solver
The Sudoku solver solves a classic 9x9 Sudoku puzzle, where the goal is to fill in the empty cells such that every row, column, and 3x3 box contains exactly the digits 1 through 9, each occurring once.
### Features
- **Backtracking Search**: Uses backtracking to fill in the Sudoku board.
- **Heuristics**: Implements Minimum Remaining Values (MRV), Degree Heuristic, and Least Constraining Value (LCV) to optimize the search.
- **Arc Consistency (AC-3)**: Reduces the domains of the variables to make the puzzle easier to solve.
### Usage
1. Clone the repository:
```bash
git clone https://github.com/yourusername/sudoku-magic-square-solver.git
cd sudoku-magic-square-solver
```
2. Run the Sudoku solver:
```python
python sudoku_solver.py
```
3. Choose the heuristic:
- `1` for MRV
- `2` for Degree Heuristic
- `3` for basic backtracking
4. The program will print the solved Sudoku board and the execution time.
### Code Explanation
- **print_board(board)**: Prints the Sudoku board.
- **find_empty(board)**: Finds the next empty cell on the board.
- **is_valid(board, num, pos)**: Checks if placing `num` at `pos` is valid.
- **find_empty_with_mrv(board)**: Finds the empty cell with the fewest legal values.
- **find_empty_with_degree(board)**: Finds the empty cell with the most constraints on its neighbors.
- **least_constraining_value(board, pos)**: Orders the values by how few constraints they place on other cells.
- **solve(board, choice)**: Solves the Sudoku using the chosen heuristic.
- **enforce_arc_consistency(board)**: Ensures arc consistency using the AC-3 algorithm.
- **preprocess_with_ac3(board)**: Preprocesses the board with AC-3 before solving.
## Magic Square Puzzle Solver
The Magic Square puzzle solver solves a 3x3 magic square puzzle using a genetic algorithm. The goal is to rearrange the numbers 1 to 9 such that the sum of the numbers in each row, column, and diagonal equals 15.
### Features
- **Genetic Algorithm**: Uses a genetic algorithm to find solutions to the magic square puzzle.
### Usage
1. Run the Magic Square puzzle solver:
```python
python magic_square_solver.py
```
2. The program will print the best magic square found and the number of generations it took to find it.
### Code Explanation
- **fitness(square)**: Calculates how close the square is to being a magic square.
- **swap_elements(square)**: Randomly swaps two elements in the square, excluding the central number.
- **Main loop**: Runs the genetic algorithm until a solution is found or the maximum number of generations is reached.
## Dependencies
- Python 3.x
- NumPy
You can install the required dependencies using:
```bash
pip install numpy
```
## License
This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.
## Contributing
Contributions are welcome! Please feel free to submit a Pull Request.