Volume 4 Issue 2

This paper proposes an intelligent decision support framework that integrates geographic information system (GIS) and building information modeling (BIM) to optimize supply chain operation in smart building design. This framework uses intelligent algorithms to synchronously balance procurement paths, supplier selection, and construction procedures, thereby minimizing embodied carbon emissions and full life cycle costs. Taking a mid-level office building as an example, under the principle of balancing environmental and economic objectives, this method reduces embodied carbon by 18% and lowers life cycle costs by 12% compared with the traditional plan. Scenario simulation further reveals a controllable balance of carbon costs: up to 25% carbon emission reduction (with a 9% cost increase), or 18% cost savings (with only a 4% carbon emission increase). Stability tests show that when price and emission parameters are perturbed by ±10%, the fluctuation range of the optimization scheme remains at ±2%. The achievements demonstrate the potential of AI-driven spatial analysis technology to guide sustainable procurement, logistics optimization, and material selection. Subsequent research will integrate real-time data streams with renewable energy factors to support dynamic reoptimization.

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