Study on the smart transformation strategy of old neighbourhoods based on urban renewal

With the rapid development of the economic level, urban renewal has become a major project in urban construction nowadays. Among urban renewal projects, the renovation of old neighbourhoods is an important part. Most traditional renovations consider only the cost impact, ignoring the influence of the residents’ wishes and environmental factors. Therefore, an intelligent preference model for retrofitting solutions becomes crucial. This study establishes a multi-objective optimisation model for the renovation of old neighbourhoods under the concept of urban regeneration, keeping in mind the theme of smart cities. The study innovatively provides a solution by optimising a genetic algorithm to obtain the optimal solution for the renovation of old neighbourhoods. Through data analysis and model testing of renovated old neighbourhoods, the results show that the method has an error of 2.04 days for the renovation duration, 0.89% for the cost and 0.43% for the quality score. The method significantly improves the efficiency of the search for excellence, while the study provides a reference path for the smart retrofitting of old neighbourhoods.