Factory layout planning using quantum annealing

Factory layout planning is a central task in manufacturing system design, affecting transportation routes, throughput times, and resource utilization. While manual methods and traditional approximative approaches often fall short of industrial demands due to time and quality constraints, quantum annealing presents a promising alternative. This paper introduces a constrained quadratic model for automated factory layout planning, incorporating multi-criteria objectives and scalability. Utilizing data from an industrial scenario, the approach is benchmarked against non-dominated sorting genetic algorithm II for greenfield and brownfield planning. The results demonstrate quantum annealing's superior performance in solution quality through reductions in transport intensity and space optimization.