Industrial Site Selection: Methodologies, Advances and Challenges

Industrial site selection holds strategic importance in the layout of industrial facilities. Scientific decision-making in site selection not only enhances the economic and technical feasibility of a project but also lays the foundation for sustainable development. However, industrial site selection is considered an NP-hard problem. The criteria used to evaluate site suitability, the methods proven effective under different conditions, big data sources introduced, and the key data gaps, methodological limitations, and research priorities to improve decision quality are important for researchers and engineers. Based on the Web of Science (WOS) core collection as the data source, this paper retrieved the literature related to the themes of “industrial site selection” and “facility location decision making”, and selected 149 highly relevant papers. It systematically categorizes three mainstream site selection methods: operations research-based methods; the application of geographic information systems in site selection; and the application of artificial intelligence in site selection. On this basis, this paper provides a systematic review of the overall industrial site selection process and methodologies, aiming to offer references for subsequent site selection analysis research and practical site selection work. An “MCDM–GIS–AI” technology convergence roadmap is also proposed for industrial site selection to identify remaining research gaps and offer a set of “good-practice guidelines” to inform both practical applications and future analytical studies.