Facilities Layout Design Optimization of Production Workshop Based on the Improved PSO Algorithm

The facility layout of the production workshop primarily focuses on the layout planning of production equipment to reduce material handling costs within the workshop. With the development of the low-carbon economy, a scientifically rational facility layout planning contributes to improving overall operational efficiency and reducing carbon emissions in the production process. However, the design of a production workshop facility layout is a complex optimization problem involving multiple objectives, such as minimizing handling costs, maximizing total non-logistics relationships, and optimizing the utilization of workers' working hours. Additionally, it must adhere to various constraints, including area utilization rates and equipment utilization constraints. Existing layout methods often fall short of meeting the practical requirements of engineering practice. Therefore, to address the optimization challenges related to the facility layout of the production workshop, this paper establishes a comprehensive optimization model, targeting low-carbon logistics within the production workshop and optimizing the overall non-logistical relationships between operational units as the optimization objectives. Subsequently, this paper proposes an improved Particle Swarm Optimization (PSO) method, considering task collaboration, to solve the integrated optimization model of the facility layout for the valve component production workshop at Company A. Finally, the validity of the model and algorithm is confirmed through example calculations and result analysis. The analysis results demonstrate that, under the same conditions, the improved PSO algorithm outperforms PSO and SGA (Simple Genetic Algorithm) algorithms in terms of optimization results, iteration counts, and runtime. In conclusion, this study introduces task collaboration to enhance the traditional PSO algorithm. Simultaneously, we consider both logistics and non-logistics relationships in optimizing facility layout design. This provides theoretical references and new solving algorithms for low-carbon logistics.