PSO Algorithm Solves 6x6 Job Shop Scheduling Problem with MATLAB Implementation

This program is implemented in MATLAB and utilizes the Particle Swarm Optimization (PSO) algorithm to solve a 6x6 job shop scheduling problem, with integrated Gantt chart visualization. The code structure includes key components such as particle position initialization representing job sequences, velocity updates with cognitive and social parameters, and fitness evaluation based on makespan calculation through schedule simulation. The implementation follows standard PSO workflow with iteration-based optimization and convergence monitoring. Designed with educational clarity, the code features modular functions for scheduling decoding and objective function calculation, making it accessible for beginners to understand both scheduling optimization concepts and metaheuristic algorithm implementation. The program's architecture allows for straightforward extension and optimization to handle varying problem scales and complexities through parameter adjustments and constraint modifications. Through further experimentation and development, users can deepen their understanding of job shop scheduling challenges and optimization algorithms, thereby enhancing both programming skills and problem-solving capabilities in operations research domains. The code provides a practical foundation for implementing additional features like local search techniques, multi-objective optimization, or hybrid algorithm approaches.