Dual-Chain Quantum Genetic Algorithm Source Code Implementation

In this documentation, I present a MATLAB implementation of the dual-chain quantum genetic algorithm source code. This resource aims to facilitate better understanding and mastery of this sophisticated optimization technique. The dual-chain quantum genetic algorithm represents a fascinating and highly effective optimization method that synergistically combines the advantages of quantum computing principles with genetic algorithm mechanisms. This algorithm employs quantum bits (qubits) represented through dual chains to maintain population diversity and enhance global search capabilities. The implementation features key components including quantum rotation gate operations, quantum crossover mechanisms, and quantum mutation procedures. Through this algorithm, various complex optimization challenges can be addressed effectively, such as function optimization, parameter tuning, and multi-dimensional optimization problems. The source code is developed using MATLAB programming language, making it accessible even for individuals with limited programming experience. The implementation includes clear comments and follows modular programming practices, with distinct functions for population initialization, fitness evaluation, quantum update operations, and convergence checking. Each module demonstrates proper handling of quantum probability amplitudes and phase adjustments throughout the evolutionary process. I hope readers find this documentation valuable and gain practical insights into quantum-inspired evolutionary computation techniques. The code structure allows for easy modification and extension to adapt to specific optimization requirements while maintaining the core quantum genetic algorithm principles.