The Use of the Multi-objective Ant Colony Optimization Algorithm in Land Consolidation Project Site Selection.

The present study abstracts the land consolidation project site selection (LCPSS) problem to a multi-objective spatial optimization problem. In view of the shortcomings of traditional site selection methods in coordinating multiple objectives, the present study, considering the scale-related constraint conditions and general site selection rules of land consolidation, proposes a multi-objective LCPSS model (MOLCPSSM) based on an ant colony optimization algorithm with social, economic and ecological benefits as the optimization objectives. In addition, the present study focuses on the investigation of the mapping and coding relationships between the artificial ants and vector patches and also improves the ants’ spatial unit selection scheme and pheromone update mechanism. Furthermore, the present study verifies the MOLCPSSM through a case study of Jiayu County, Hubei Province, China. The results demonstrate the operability of the MOLCPSSM in solving practical land consolidation problems.