Robust optimization of agriculture products urban distribution path considering demand uncertainty

Abstract

Given the optimization problem of agriculture products logistics distribution path in the city, the demand of retail terminals is uncertain because consumer demand is affected by environmental and social factors, and the agriculture products urban distribution optimization model based on the determined demand cannot effectively solve the distribution problem with uncertain demand. Based on the demand determination model, this paper constructs a robust optimization research model based on scenario sets and reallocates distribution paths according to the change of demand. A robust optimization model of the agriculture products urban distribution path under multiple scenarios is built on the basis of meeting the mixing time window and using the objective function of total cost agriculture products urban distribution optimization model. To solve the problem, an improved genetic algorithm was designed by introducing elite retention strategy and migration strategy, which improved the defect of the traditional genetic algorithm which was easy to precocious convergence. Compared with the genetic algorithm, the proposed algorithm achieved the minimum total cost in all scenarios, the average total cost was reduced, the average convergence time of the algorithm was reduced by 5%, and the average total vehicle running distance was reduced by 3%.