Optimization Problems with Genetic Algorithms

An exploration of single-objective optimization with genetic algorithms.

---

Genetic Algorithm Steps

1. Initialization
2. Evaluation
3. Selection
4. Crossover
5. Mutation
6. Replacement

---

Repository Files

• Problem 1 : imports genetic algorithm function from genetic_algorithm.py module with steamlit interface
• Problem 2 and Problem 3 : implements geneticalgorithm 1.0.2 library