This repository contains a C++ implementation of a Genetic Algorithm (GA) designed for solving continuous optimization problems.
The project focuses on core evolutionary computation concepts, including population-based search, genetic operators, and fitness-based selection. The implementation emphasizes clarity and algorithmic correctness.
- Population initialization
- Fitness evaluation
- Selection mechanisms
- Crossover and mutation operators
- Elitism to preserve high-quality solutions
- Multiple independent runs for statistical evaluation
- Practice evolutionary algorithm design
- Understand convergence behavior of Genetic Algorithms
- Analyze the impact of parameters such as population size and mutation rate
- C++
- Standard library random number generation
- Numerical optimization techniques
This project was developed for academic purposes in the context of evolutionary algorithms and optimization.