A Vehicle Routing Optimization Framework of a Property City Based on an Intelligent Algorithm and Its Application

Property city is a newly emerging property service mode attracting widespread attention. Addressing the gap in quantitative analysis of the vehicle routing problem (VRP) of a property city based on quantitative analysis in existing studies, this study introduces the single-loop traveling salesman problem (TSP) and multi-loop VRP models for different service scenarios of a property city. An intelligent optimization framework combining the nearest insertion method and genetic algorithm was constructed to solve these problems. The example analysis results show that the intelligent algorithm is feasible, outperforming the nearest insertion method in designing reasonable operational schemes, while the total operational cost of the multi-loop scenario was lower than that of the single-loop scenario. This study enriches the theoretical system of property city and provides references for its service practice.