关键词: 两级冷链规划, 时间窗, 社区团购, 低碳, 众包, 改进的自适应大领域搜索算法

Abstract: Considering the current community group purchase fresh products cold chain transportation process, due to quality decay leading to customer satisfaction is reduced, while the demand blowout causes insufficient capacity, a two-level cold chain collaborative optimization distribution strategy based on the crowdsourcing model is proposed, that is, the enterprise refrigerated truck completes the first-level cold chain transportation from the city warehouse to transit warehouse, and the crowdsourced refrigerated truck completes the secondary cold chain transportation from the transfer warehouse to the head of the regiment, and the total cost including service delay cost, carbon emission cost and fixed cost is minimized. And the customer’s satisfaction with the product quality is the optimization goal, and a two-stage open-close hybrid cold chain vehicle low-carbon path planning model with crowdsourcing is established. According to the characteristics of the model, an improved adaptive large neighborhood search (IALNS) algorithm is constructed, a new destruction-repair solution strategy is designed, and the idea of simulated annealing (SA) is added in the operator selection stage to speed up the convergence speed and improve the global search capability of the algorithm. By comparing the results with the example optimization results of adaptive large neighborhood search (ALNS) , simulated annealing (SA) , genetic algorithm (GA) , and particle swarm optimization (PSO) , it is proved that this method is feasible and effective. The strategy takes into account corporate profits and customer needs, and compares the experimental results in different distribution modes, which verifies that the model has positive significance in solving the problem of cold chain logistics of community group purchase fresh products.

Key words: two-echelon cold chain planning, time window, community group purchase, low carbon, crowdsourcing, improved adaptive large neighborhood search