Design of Spatial Layout System for Sustainable Environmental Optimization Based on Multi-Strategy GWO Algorithm

The problem of sustainable environmental optimization spatial layout has become a hot topic of concern today. The Grey Wolf Optimizer (GWO) algorithm based on multi-strategy is introduced to improve the optimization ability of the environmental layout system in resource allocation and energy consumption. Through the improved GWO algorithm, multiple strategies are combined to perform collaborative optimization of global search and local search to solve complex multi-objective optimization problems. In order to solve the problems of low efficiency and poor accuracy of traditional algorithms in environmental layout design, this study proposes a new multi-strategy GWO method, which can effectively balance the weights of multiple optimization objectives and improve the overall performance of the system on this basis. Firstly, in view of the limitations of the traditional GWO algorithm, the search process is optimized by combining the differentiated mutation strategy to avoid falling into the local optimal solution. Then, the adaptive weight mechanism is adopted to dynamically adjust the weight of each objective function in each iteration to cope with the dynamic changes in the multi-objective optimization problem. Finally, a sophisticated search strategy is used to efficiently explore the solution space. The convergence speed of the algorithm is enhanced by introducing an external elite group, and the search results are fine-tuned to ensure the optimal layout design. In the initial stage (100 times of delivery), the resource utilization efficiency is 0.80, the environmental impact is 0.60, and the comprehensive target value is 0.75. As the number of delivery increases, the resource utilization efficiency gradually increases to 0.90, and the environmental impact gradually decreases to 0.40. The comprehensive target value also increases accordingly, from 0.75 to 0.85. The method proposed in this paper can effectively improve the efficiency and accuracy of layout design, and provide a new optimization idea and practical solution for sustainable environmental management.