An intelligent decision-making framework for territorial spatial layout coupling simulation and optimization: a case study of Hui’an County

Introduction The primary challenge in territorial spatial planning is optimizing land allocation under complex constraints. This study aims to bridge the gap between predictive simulation and normative optimization to support scientific planning. Methods This study developed an intelligent framework coupling an Artificial Neural Network-Cellular Automata (ANN-CA) model with a Multi-Agent System (MAS) based on an ant colony algorithm. Applied to Hui’an County, China, the framework first simulates a 2035 baseline land use scenario under policy and physical constraints. Subsequently, the MAS optimizes the construction land layout based on multi-objective functions for economic, ecological, and morphological goals. Results The optimization yielded significant quantitative improvements compared to the baseline scenario. The spatial configuration of construction land became more regular, with the Area-Weighted Mean Shape Index (AWMSI) decreasing by 35.7% from 79.44 to 51.11. The layout also became more compact and less fragmented, evidenced by a 1.0% increase in the Aggregation Index (AI) to 95.03 and a 27.1% reduction in the number of patches. Discussion This integrated framework provides an effective technical pathway for scientific planning. By coupling simulation with optimization, it ensures that future development patterns are not only efficient and responsive to historical trends but also adhere to strict ecological and farmland protection policies, leading to a more sustainable and well-structured territorial spatial layout.