Genetic Algorithm Source Codes Including GA, SGA, AGA, TSPGA, GAPID, NSGA, and NSGA2

This repository contains multiple genetic algorithm source codes that I have either collected or personally developed. The collection includes various GA implementations such as: - Standard Genetic Algorithm (GA): Basic implementation with selection, crossover, and mutation operators - Simple Genetic Algorithm (SGA): Simplified version focusing on fundamental evolutionary operations - Adaptive Genetic Algorithm (AGA): Features dynamic parameter adjustment for crossover and mutation rates - Traveling Salesman Problem GA (TSPGA): Specialized implementation for combinatorial optimization problems using permutation encoding - PID Controller Optimization GA (GAPID): Applies GA to optimize proportional-integral-derivative controller parameters - Non-dominated Sorting GA (NSGA): Multi-objective optimization algorithm with Pareto-based ranking - NSGA-II: Enhanced version with crowding distance computation and elite preservation for better diversity maintenance Each implementation includes core genetic operators such as tournament selection, simulated binary crossover, and polynomial mutation, with appropriate chromosome encoding schemes for different problem domains. The codes demonstrate proper fitness evaluation, population initialization, and convergence monitoring mechanisms.