Mixed Integer Robust Programming Model for Multimodal Fresh Agricultural Products Terminal Distribution Network Design

Abstract

The low efficiency and high cost of fresh agricultural product terminal distribution directly restrict the operation of the entire supply network. To reduce costs and optimize the distribution network, we construct a mixed integer programming model that comprehensively considers to minimize fixed, transportation, fresh-keeping, time, carbon emissions, and performance incentive costs. We analyzed the performance of traditional rider distribution and robot distribution modes in detail. In addition, the uncertainty of the actual market demand poses a huge threat to the stability of the terminal distribution network. In order to resist uncertain interference, we further extend the model to a robust counterpart form. The results of the simulation show that the instability of random parameters will lead to an increase in the cost. Compared with the traditional rider distribution mode, the robot distribution mode can save 12.7% on logistics costs, and the distribution efficiency is higher. Our research can provide support for the design of planning schemes for transportation enterprise managers.