Real Estate Location Optimization Model Based on Linear Programming Model Mombined with Property Insurance Pricing

Real estate location selection is integral to real estate decision-making. Accurate real estate site selection is of great significance to ensure profits for real estate developers, increase real estate flexibility, and improve the serviceability of the real estate industry. To accurately locate real estate, this paper takes Dallas County, which is a high-risk area, as the research object, and establishes a real estate location optimization model combined with property insurance pricing model. This model selects nine indicators that affect housing prices and uses ArcGIS software to simulate the housing price score of the area based on these nine factors. Then, three factors, including property insurance premium, disaster resistance coefficient, and regional risk level, were introduced, and a real estate location optimization model with the highest profit as the objective function was established. Based on this model, the specific values of the disaster resistance coefficient, housing prices, and low-profit housing prices are calculated to achieve optimal real estate decisions in Dallas County. This model can provide various communities and real estate developers with profitable real estate decisions under frequent extreme weather conditions.