Research on Multi-objective Layout Optimization Model of Rural Industry based on Improved Ant Colony Algorithm Under the Background of Digital Economy

The optimal allocation of rural land use plays a unique role in developing rural industries. Therefore, realizing the effective use of land resources is the key to sustainable development. This research attempts to explore the modeling of rural land use in combination with an ant colony algorithm and multi-objective optimization problem under the background of the current digital economy and to explore land use and space allocation after optimal allocation. The experimental results showed that the multi-objective optimization model of land use proposed in this study could optimize the relevant objective functions so the entire optimization system can reach the optimal solution. The iterations of different objective functions under the three optimization models were compared. The four objective functions of carbon emission, minimum planning cost, adaptability value, and spatial agglomeration all iterated approximately 45 times. They began to converge under the premise of taking the land adaptability value and spatial agglomeration as optimization goals. The convergence rate was faster under this optimization model. In addition, the iteration and running time of the traditional ant colony algorithm, the genetic algorithm, and the improved ant colony algorithm under two different objective functions were compared. Copyrights © 2024 The Institute of Electronics and Information Engineers.