MATLAB Simulation of Quantum Particle Swarm Optimization Algorithm

This MATLAB simulation program implements the Quantum Particle Swarm Optimization (QPSO) algorithm with comprehensive Chinese annotations. The QPSO algorithm is an optimization technique that mimics quantum mechanical particle behavior to search for optimal solutions. Developing this simulation in MATLAB allows for better understanding and practical application of the algorithm. The implementation includes detailed Chinese annotations to help users understand both the programming details and theoretical principles. Key algorithmic components feature explanations of quantum behavior simulation through wave function probability distributions and quantum state updates using potential well models. The MATLAB code structure demonstrates: - Quantum state initialization using random position generation within solution bounds - Wave function collapse implementation through probability density functions - Quantum potential well modeling for particle convergence - Global best position tracking with quantum-inspired update mechanisms Users can adjust parameters like population size, iteration limits, and quantum contraction-expansion coefficients to optimize performance for specific problems. The program's modular design allows easy modification of fitness functions and constraint handling. This well-documented simulation facilitates algorithm research and promotes practical applications in optimization problems across various engineering and scientific domains.