At present, many developing countries around the world are experiencing urbanization, and China has the largest scale of urbanization. The current literature mainly focuses on the relationship between economic factors, environmental factors and urbanization, ignoring the human factors. In fact, whether sufficient social security can be provided to solve people’s worries, as well as people’s social attitudes, has an important impact on their migration from rural areas to urban areas. By using the China General Social Survey (CGSS) 2018 data and constructing a binary logistic model, this paper studies the impact of social security on migration from rural areas to urban areas, as well as the mediating effects of people’s social attitudes. The results reveal that: (1) Social security has a significant positive effect on migration from rural areas to urban areas. (2) The improvement of the sense of fairness, happiness and security is conducive to the integration willingness and identity of the rural population and promotes urbanization. Therefore, social attitude plays an important mediating role. According to our study, policymakers need to consider how to build a suitable social security system and make rural residents feel safe and happy, so as to promote the sustainable development of urbanization.

This study, taking the R fresh agricultural products distribution center (R-FAPDC) as an example, constructs a multi-objective optimization model of a logistics distribution path with time window constraints, and uses a genetic algorithm to optimize the optimal trade distribution path of fresh agricultural products. By combining the genetic algorithm with the actual case to explore, this study aims to solve enterprises’ narrow distribution paths and promote the model’s application in similar enterprises with similar characteristics. The results reveal that: (1) The trade distribution path scheme optimized by the genetic algorithm can reduce the distribution cost of distribution centers and improve customer satisfaction. (2) The genetic algorithm can bring economic benefits and reduce transportation losses in trade for trade distribution centers with the same spatial and quality characteristics as R fresh agricultural products distribution centers. According to our study, fresh agricultural products distribution enterprises should emphasize the use of genetic algorithms in planning distribution paths, develop a highly adaptable planning system of trade distribution routes, strengthen organizational and operational management, and establish a standard system for high-quality logistics services to improve distribution efficiency and customer satisfaction.