An Improved Distribution Cost Model Considering Various Temperatures and Random Demands: A Case Study of Harbin Cold-Chain Logistics

This paper explores a more applicable distribution scheme to reduce the distribution cost from the perspective of various influencing factors in the distribution process. We comprehensively considers the effect of temperature changes on the decay rate of fresh products during unloading, the carbon emission costs during transportation and cold storage, customer satisfaction, as well as the traffic situation of the actual distribution route. On this basis, a distribution cost model is constructed. And the improved genetic algorithm is used to solve the problem. In addition, we also conducted sensitivity analysis on different customer demands, so as to put forward some management enlightenment to business managers. An analytical investigation of a case study in Harbin indicates that reasonable transportation path planning can effectively reduce the total distribution cost. Hence, the proposed distribution scheme can serve as an effective and socially feasible method in cold chain logistics management to reduce logistics costs.