Swarm Intelligence-Based Optimization of Matrix System Layout with Workstation Combination and Assignment

The layout of a manufacturing system is a critical factor that significantly influences system performance during operation. Achieving an optimal layout requires simultaneous consideration of equipment selection, such as determining the appropriate combination of workstations, and workstation assignment for a layout design. However, existing research often assumes a predetermined workstation combination, focusing solely on optimizing workstation assignments for a layout design. Since workstation combination is typically undecided in the early stages of layout design, particularly in greenfield systems, an integrated optimization approach is essential.This study proposes a layout design optimization methodology for Matrix Manufacturing Systems (MMS) that simultaneously considers workstation combination (i.e., equipment selection) and workstation assignment problems. The proposed approach integrates Particle Swarm Optimization (PSO) with production simulation, employing a dimensionally reduced and information-dense solution representation—a structured format that encapsulates candidate solutions—to optimize both aspects simultaneously. To validate the proposed methodology, we conducted a case study on an automotive assembly process, comparing our approach with an existing method that separately solves workstation combination and assignment problems.