Optimization of Delivery Path for Community Group Buying Cold and Fresh Products Under Multi-Objective Conditions

In response to the problems of high transportation costs, high product losses, and low customer satisfaction in the distribution process of community group buying cold and fresh products, a multi-objective distribution path optimization model was constructed to minimize the total distribution cost and maximize customer satisfaction, including the use cost of refrigerated trucks, cargo damage cost, carbon emission cost, and time window cost. The model was solved using a non dominated sorting genetic algorithm with elite strategy (Elitist Non-dominated Sorting Genetic Algorithm, NSGA-II), and compare and analyze the solution results with traditional multi-objective genetic algorithms. The simulation results of the example validate the effectiveness of the model and algorithm proposed in this paper, effectively reducing the total delivery cost and improving customer satisfaction.