A dry port hub-and-spoke network design: an optimization model, solution method, and application

This paper studies an innovative bi-objective optimization model for the dry port hub-and-spoke network that considers both the minimization of the total costs and the total amount of carbon emissions. The model is formulated as a two-stage stochastic program due to the uncertain nature of demand. Here, the decision variables include the optimal locations of dry ports, their respective numbers, and their connections, together with the flows of containers. Two types of dry ports are taken into account, where there may be container flows from a relatively small dry port (feeder dry port) to a large dry port (hub dry port). As the problem is NP-hard and practically too complex to solve by an exact method, an efficient hybrid Genetic Algorithm (GA) with interesting ingredients is developed to obtain a promising set of non-dominated solutions. The performance of the proposed methodology is evaluated on a case study of Tianjin Port, China. The computational experiments reveal that the proposed method is promising while providing a useful practical optimization tool that can provide insightful directions for governmental and industrial stakeholders as well as logistic companies on which dry ports can make a suitable addition to their portfolio.