A land-use spatial optimum allocation model coupling a multi-agent system with the shuffled frog leaping algorithm

The optimum allocation of land resources is an important process that promotes the intensive use of land resources and facilitates sustainable development. The main land-use optimum allocation models generally tend to ignore the influence of human activities on the optimization of land-use; thus, leading to inaccurate optimization results for the land-use spatial layout and impeding sustainable land-use planning. Some of these models consider human activities, but lack global optimization goals and iterative search mechanisms, and therefore have no optimization function and provide unsatisfactory optimization results. Therefore, this study coupled the multi-agent system (MAS) that contains land-use planning knowledge with the search iteration mechanism in the shuffled frog leaping algorithm (SFLA) and rebuilt the local optimization behavior of the SFLA; thus, developing a new kind of land-use optimum allocation model, the so-called multi-agent shuffled frog leaping algorithm (MASFLA). The model was then applied to the Jizhou District of Tianjin City, and there were three key simulation results. (1) The MASFLA had remarkable optimization effects on land resource use, and the optimized values of ecosystem services, regional economic output, and land-use intensive degree increased by 18.6, 51.1, and 30.3%, respectively. (2) The MASFLA had better optimization effects than a single algorithm, and its comprehensive fitness value was 2.1 and 4.1% higher than that of the SFLA and the particle swarm optimization (PSO), respectively, under the same convergence conditions. (3) The MASFLA model could relieve the land-use conflicts between different decision-making agents and realize the optimum allocation of regional land-use in terms of both spatial structure and quantity under multiple optimization goals and restrictions; thus, increasing the local economic output, improving the land-use spatial compactness and ecological environment, and promoting the sustainable use of regional land.