Optimization of Facility Layout in Manufacturing: A Case Study Combining Genetic Algorithms and Systematic Layout Planning

Facility layout optimization plays a crucial role in enhancing production efficiency, minimizing costs, and ensuring smooth workflow in manufacturing systems. This study focuses on optimizing the facility layout of a traditional manufacturing enterprise through an innovative hybrid approach that combines Systematic Layout Planning (SLP) with Genetic Algorithms (GAs). SLP was initially employed to evaluate logistics and non-logistics relationships based on data collected directly from the manufacturer. This step provided preliminary layout plans, which served as the foundation for further refinement. Genetic Algorithms were then applied to optimize these layouts by iteratively improving the arrangement of facilities. The final optimized layout demonstrated an 8.61% increase in logistics efficiency compared to the initial design. To ensure solution robustness, comparative analyses were conducted, showcasing the reliability and adaptability of the hybrid approach. This research highlights the significant advantages of integrating GAs into the SLP process, offering a practical and effective framework for facility layout optimization in complex and dynamic production environments. The findings provide valuable insights for manufacturers seeking to improve operational efficiency through data-driven and systematic layout design.