Regional land-use allocation using a coupled MAS and GA model: from local simulation to global optimization, a case study in Caidian District, Wuhan, China

Abstract

China is facing the pressures of both rapid economic development and environmental protection, and land-use allocation optimization is an important way to manage the conflicts between these pressures and to achieve sustainable development. Optimization of land-use allocation is a nonlinear multiobjective spatial optimization problem, and a purely local simulation model or global optimization model is insufficient to solve it. It is essential to bridge the gap between the two models through the combination of top-down and bottom-up approaches. This study integrates a multiagent system (MAS) that simulates the behaviors of land-use stakeholders with regard to their choices of specific locations, with a genetic algorithm (GA) that simultaneously evaluates and optimizes land-use configurations to meet various regional development objectives. The model is expected to achieve the optimization of land use in terms of the composition and spatial configuration. Caidian District, Wuhan, China, was chosen as the study area to test the model in this paper. The results show that the performance of the coupled model is superior to a pure GA model or MAS model. The optimal configuration improves on the economic output, spatial compactness, and carbon storage of the current configuration and promotes sustainable regional land-use development from the local scale to the regional scale.