关键词: 协同运输, 联合运输, 轴辐式网络, Benders分解

Abstract: Collaborative transportation is a good way of saving logistics costs by integrating all transportation demands and transportation resources to achieve economies of scale. Under the scale effect, the unit transport cost is lower if we construct a hub arc by paying a fixed charge and take more flow to the arc. And transportation tasks have to carefully choose their route since zigzag route has larger distance than direct route. In this paper, collaborative transportation routing integration problem are studied with fixed arc costs and distance limitation(CTRIP), which seeks the optimal transportation route of all O-D flow to minimize the total costs including routing costs of tasks and fixed costs of hub arcs, while the routing distance is required to be within a limited range. CTRIP arises in the application on airline transportation, road transportation, postal services and pipeline transport. A mixed-integer programming model is formulated for CTRIP, and a heuristic algorithm is provided based on Benders Decomposition. Then, a computational experiment is carried out based on AP data set from OR-Library, and the results show the algorithm works well. Further, CTRIP is compared with current relative researches about Hub-and-Spoke Network Design Problem (HASNDP) on a special instance. It is found that CTRIP can better guarantee scale advantages of hub arcs than CTRIP which has a flaw hypothesis.Unlike HASNDP which concentrate on integrating tasks through hubs, combing transport through hub arcs is the focus of this paper. The study can provide a new perspective research about collaborative transportation by shifting our method from integrating tasks through nodes to combing transport through arcs.

Key words: collaborative transportation, combined transport, hub-and-spoke network, Benders Decomposition