Production Scheduling Using Particle Swarm Optimization

This source code provides a comprehensive demonstration of production scheduling using Particle Swarm Optimization (PSO) algorithm, offering detailed explanations to facilitate better understanding of PSO's core concepts. The implementation clearly illustrates the working mechanism of particle swarm optimization through well-structured code that includes key components such as particle initialization, velocity updates, position updates, and fitness evaluation functions. The code demonstrates practical application scenarios including factory production scheduling and logistics optimization, showcasing how PSO efficiently handles complex scheduling problems through swarm intelligence. Through detailed code analysis and real-world case studies, readers can gain deeper insights into PSO's role and advantages in production scheduling, including its ability to handle constraints, convergence behavior, and parameter tuning strategies. The implementation also discusses common optimization techniques such as inertia weight adjustment and neighborhood topologies, enabling readers to effectively apply and enhance the algorithm for various industrial scheduling challenges.