Optimization of stamping workshop line layout based on improved PSO algorithm

Optimizing the layout of stamping workshops is crucial for enhancing production efficiency and reducing material handling costs. This study proposes a mathematical model and introduces an enhanced Particle Swarm Optimization (PSO) algorithm to address this challenge. The improved PSO dynamically adjusts inertia weights and learning factors, effectively balancing global exploration and local exploitation to achieve more accurate and efficient optimization. Through MATLAB simulations, the proposed method was validated on a real-world stamping workshop case, resulting in a 25.01% reduction in logistics handling costs compared to the initial layout. Additionally, the enhanced algorithm outperformed traditional PSO in terms of convergence speed and solution quality. This work offers a novel and practical framework for workshop layout optimization, contributing significantly to cost reduction and productivity improvement in industrial applications. The findings also provide valuable insights for advancing intelligent workshop design and supporting the transition to digital and automated manufacturing environments.