An Iterative Backbone Algorithm for Service Network Design Problems

Abstract

Service network design problems arise at airlines, trucking companies, and railroads wherever there is a need to determine cost-minimizing routes and schedules, given resource availability and service constraints. In recent years, the application of consolidation-based service network design in the express service has attracted lots of academic attention due to the rapid growth of the express industry. This paper studies the consolidation-based service network design problem, which jointly determines the commodity flow, vehicle dispatching, and fleet sizing. We propose a mixed-integer optimization model to address the problem and design an efficient iterative backbone algorithm to solve large-scale real-world problems. The numerical results of large-scale instances confirmed that the solution obtained by our proposed algorithm is better than that of the primal model, and the running time taken is less than half that of the general solution approach. The computational study confirmed the effectiveness and efficiency of the proposed algorithm.