Two-Echelon Location-Routing Problem with Fuzzy Demand of Rural E-Commerce Logistics

To promote the green and high-quality development of rural e-commerce logistics, we propose the Two-Echelon Location-Routing Problem with Fuzzy Demand (2E-LRP-FD) of the rural e-commerce logistics network. Considering fuzzy demand, government subsidies and simultaneous delivery, the objective function aims to maximise the profit of enterprises considering government subsidies. The fuzzy chance-constrained programming method is used to deal with the triangular fuzzy variables of pickup demands. Additionally, we present a two-stage Improved Non-Dominated Sorting Genetic Algorithm II (INSGA-II) that integrates stochastic simulation and a K-means clustering algorithm to effectively solve the problem. In the end, the numerical experiments of algorithm and model design are verified. The experimental results demonstrate that the proposed INSGA-II is significantly efficient and effective. Furthermore, we discuss the relationship between subsidy strategies and logistics enterprise profits. This research contributes valuable insights for the establishment of rural e-commerce logistics systems.