An Optimization Model for the Vehicle Routing Problem in Multi-product Frozen Food Delivery

This paper addresses a vehicle scheduling problem encountered in the cold chain logistics of the frozen food delivery industry. Unlike the single product delivery scenario, we propose an optimization model that manages the delivery of a variety of products. In this scenario, a set of customers make requests for a variety of frozen foods which are being loaded together. The objective is to find the routes that represent the minimum delivery cost for a fleet of identical vehicles that, departing from a depot, visiting all customers only once and returning to the depot. The delivery cost includes the transportation cost, the cost of refrigeration, the penalty cost and cargo damage cost based on the characteristics of different frozen food products. Apart from the usual constraints of time windows and loading weight, the study also takes into account the constraints of loading volume related to the unit volume of different frozen foods. We then propose a Genetic Algorithm (GA) method for the model. Computational tests with real data from a case validate the feasibility and rationality of the model and show the efficient combinations of parameter values of the GA method.