A Multicommodity Multimode Network Assignment Model For Strategic Planning Of Freight Flows

With the rapid development of logistics, the mechanism of freight transportation has a larger change. For example, the carrier developed from single transportation corporation to many corporation cooperation; the decision-maker changed from the narrow shipper to the broad shipper, those changes inevitably influence the freight transportation demand. At the same time, the appropriate result of the freight network assignment model is the basis of transportation network optimization, logistic parks capacity design and location. Therefore, the study on strategic freight network assignment problem has the important practical sense based on the inner decision mechanism.A bi-level nonlinear planning model are introduced to describe the actual decision processes made by shippers and carriers and the relation between them that hurdle the previous models don't consider simultaneously that the shippers benefit is the most important on the freight transportation and the impact of the decisions made by shippers result from the change of travel time and cost incurred by decisions made by carriers. The upper level models the shipper decision in a aggregate network, the lower level models the carrier decision in a detailed (physical) network. The relationship between the upper level and the lower level is presented according to the transportation time and cost in the network. The upper level and the lower level are combined by the attribute relationship between the aggregate network and the physical network.Considering the shippers neither have information about, nor control over the detailed network. The shipper"perceived impedance"is presented by the interval number in the aggregate network. The"expectation perceived impedance"definitions and characters are given, the interval number comparison formula is introduced, the routing choice computing method based on interval number is deduced, and the stochastic user equilibrium model is given. Then the model bi-level nonlinear planning model is improved.Combined the solution algorithms both the bi-level nonlinear planning model and traffic network equilibrium models, a mixed solution algorithm of the direction search algorithm nested in direct search method was designed. A given network includes two conveyances (train, truck), three modes (railway, highway, railway-highway) and three goods needed to be transportation. The above models and described solution approaches were applied to this test network, and the path flows and costs were obtained. The solutions of both models were compared finally.