Factory layout planning is a critical task in production engineering that requires balancing multiple objectives, spatial constraints, and evolving operational needs. Despite advances in algorithmic optimization, real-world planning remains a fragmented process in which logical structuring, geometric realization, and iterative improvement are often treated in isolation. This paper presents a structured, threephase framework for integrated layout design, developed following a Design Science Research approach. The framework comprises logical layout planning, algorithmic generation of spatial configurations, and simulation-informed optimization, with each phase linked through defined data and decision interfaces. An extensive literature review forms the basis for identifying suitable algorithms for each phase, including rule-based planning methods, clustering and graph models, heuristic and parametric layout generation techniques, and a range of optimization strategies from exact solvers to metaheuristics and hybrid simulation-optimization models. The proposed model not only provides a systematic approach to integrating algorithmic and human contributions in layout planning but also serves as a strategic tool for both researchers and practitioners, enabling context-sensitive method selection and facilitating datadriven decision-making in dynamic production settings.
Rechkemmer et al. (Wed,) studied this question.
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