Quantum Immune Genetic Algorithm - Original MATLAB Implementation

This represents a completely original MATLAB implementation of the Quantum Immune Genetic Algorithm, specifically designed to solve function minimization problems. The program is fully executable and has been successfully updated with improved functionality. The algorithm integrates quantum computing principles with immune system mechanisms and genetic operations, featuring key components such as quantum-bit representation for solution encoding, immune antibody diversity maintenance, and genetic crossover/mutation operators. The implementation includes fitness evaluation functions, quantum rotation gate operations for population evolution, and memory cells for preserving optimal solutions. The code structure comprises initialization modules for quantum population generation, immune operator functions for clonal selection and suppression, and genetic algorithm components for crossover and mutation operations. The main optimization loop iterates through quantum measurement, fitness calculation, and quantum gate updates to converge toward the global minimum of the target function.