Optimization of Routing Problem for Cold Chain Logistics Considering Customer Value

There are some problems in urban cold chain logistics such as low timeliness and low customer value. This paper establishes the fresh cold chain logistics delivery routing optimization model with the minimum total cost and maximum potential customer value as the objective function, based on the perishable characteristics of fresh products and the customer value theory. The model considers vehicle load, mileage limit, and customer time window constraints. Then a hybrid genetic-simulated annealing algorithm is designed to solve the model, and an example is used to verify the effectiveness of the algorithm. In addition, the comparative analysis of the results obtained by the genetic algorithm and the genetic-simulated annealing algorithm shows that the latter can search for a better solution. The method proposed in this paper can maximize the value of customers and reduce the cost of delivery.