<p>Under the background of “double carbon” target, optimizing the land use structure of mining area becomes an important way for mining enterprises to achieve emission reduction and sink enhancement. In this study, the traditional non-dominated sorting genetic algorithm II (NSGA-II) is improved. Firstly, the stochastic region reorganization operator is introduced, which is based on the gene exchange of patches and effectively avoids land fragmentation; secondly, the trend variation operator is introduced, which makes the raster image element values closer to the land type genes with the highest peripheral values when there are multiple land types in conflict in the region of variation, and this operator can reduce the probability of spatial fragmentation after optimization. The improved NSGA-II algorithm is applied to the Wangyu mining area to construct a multi-objective optimization model. The objective functions of the model include maximizing carbon storage, maximizing economic benefits, and maximizing land aggregation. After optimization, it is found that: (1) In terms of land use structure, the area of land for mining activities is effectively controlled, such as the maximum reduction of open pit area by 41.18%. The amount of ecological land is obviously increased, such as the maximum increase of forest land by 64.27%, and the new PV land area can be increased by a maximum of 25.29hm². (2) From the data of carbon stock and carbon emission, compared with the pre-optimization, the carbon emission is significantly reduced by 27.41%, and the carbon stock is increased by 13.07%. (3) The spatial layout of the optimized mining area presents a reduction of mining land, an expansion of forest land area, and an addition of photovoltaic land. This study provides a scientific and reasonable spatial layout scheme for the mining area to realize the carbon neutral goal, and provides an important reference for the ecological restoration of the mining area based on carbon sink enhancement and carbon emission reduction.</p>