A Two-Stage Insga-Ii Approach for Two-Echelon Location-Routing Problem with Fuzzy Demand of Rural E-Commerce Logistics

In this paper, we propose the Two-Echelon Location-Routing Problem with Fuzzy Demand (2E-LRP-FD) of the " county-township-village" e-commerce logistics network. Firstly, a bi-objective model of profit maximization of logistics enterprises considering government subsidies and carbon emissions costs minimization is constructed. Secondly, the fuzzy chance-constrained programming method is used to deal with the triangular fuzzy variables of pickup demand of third level nodes. Meanwhile, a two-stage Improved Non-dominated Sorting Genetic Algorithm II (INSGA-II) based on stochastic simulation is designed by combining the K-means clustering algorithm to solve the problem. Thirdly, Nguyen's standard instances are modified, and the validity of the model and algorithm is verified by taking 25-5MN as numerical examples. Finally, sensitivity analysis of government subsidies and carbon emissions costs are discussed. The following conclusions are reached: (1) In the objective function, the profit of logistics enterprises is 1085.44 CNY, and the carbon emissions cost is 359.30 CNY. (2) INSGA-II has a significant advantage in solving efficiency and result quality. (3) When the government's subsidy for the two-layer network is 0.4 CNY/kg and 0.5 CNY/kg respectively, the government provides relatively minimal subsidies while ensuring that the enterprises remain profitable. (4) When the confidence level is between 0.4 and 0.7, there is no significant difference in carbon emissions costs between the two fuzzy programming methods. (5) When the interval width of fuzzy demand variability is less than 0.6, the overall logistics carbon emissions costs show an increasing trend. This research can provide construction references and improve the service quality of rural e-commerce logistics