Locating Hubs in Transport Networks: an Artificial Intelligence Approach

Hub facilities serve as switching and transshipment points in transportation and communication networks as well as in logistic systems. Hub networks have an influence on flows on the hub-to-hub links and ensure benefit from economies of scale in inter-hub transportation. The key factors for designing a successful hub-and-spoke network are to determine the optimal number of hubs, to properly locate hubs, and to allocate the non-hubs to the hubs. This paper presents the model to determine the locations of the p-hub facilities in the network and to allocate the non-hubs to the hubs. The problem is solved by the Bee Colony Optimization (BCO) algorithm, and the results are compared with the optimal solutions obtained by CPLEX. The BCO algorithm belongs to the class of stochastic swarm optimization methods. The proposed algorithm is inspired by the foraging habits of bees in the nature. The BCO algorithm was able to obtain the optimal value of objective functions in all test problems. The CPU times required to find the best solutions by the BCO are acceptable.