Abstract
To solve the problems that usually arise in large-scale space-optimized decision-making, such as complexity, multiple objectives, difficulties in process quantification, and time-consuming computation, this paper proposes a scenario-based, multi-objective, spatially optimized decision-making method. In line with the principle of first optimizing through spatial division into levels, and then optimizing by integration, the object of decision-making was divided in space according to its spatial characteristics. By comprehensively accounting for the general and specific conditions of the different spatial divisions that were thus created—such as decision-making objectives, global decision-making variables, local decision-making variables, global constraints, and local constraints—a framework for multi-objective spatially optimized decision-making was constructed. Specifically, both the global generality and local individuality of the object of decision-making can be taken into account through spatial division. Thus, the goal of progression from the local optimum to the global optimum can be reached. This framework was then applied to ecological restoration of the Yongding River in Beijing, China. The application indicated that the proposed approach and procedure adopted in this study are rational, feasible, and practical, showing that there existed a significant difference of the total numbers of the scenario decision-making schemes between the two cases (with and without applying the proposed framework) and considerably improving the efficiency of large-scale decision-making practices.
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