A multi-capacity integrated vehicle routing and loading model for pickup milk run

Abstract

In order to make milk run (MR) effective in current business environments characterized by uncertainty and growing complexity, models are needed that capture the different elements of such a strategy and their interactions. Among them, order assignment to vehicles and dispatching are key operational planning decisions and their integration in a single model still needs attention by researchers. Thus, this paper presents a pickup MR model that finds the order assignment and routing strategies optimizing transportation and vehicle stopping costs. A mixed integer programming (MIP) model is developed and compared with a hybrid genetic local search algorithm (HGSA). The HGSA, that performed better than MIP in terms of elapsed time for large problems, is applied to the case of an Italian manufacturing company. The outcomes show a reduced distribution cost compared with the total material cost and high vehicle utilization rates. Future research will test and validate the model in multiple application settings.