Express service providers manage shipments from senders to receivers under strict service level agreements. Such shipments are usually not sufficient to justify a single transportation, so it is preferred to maximize consolidation of these shipments to reduce cost. The consolidation is organized via depots and hubs: depots are local sorting centers that take care of the collection and delivery of the parcels at the customers, and hubs are used to consolidate the transportation between the depots. A single transportation between two locations, carried out by a certain vehicle at a specific time, is defined as a movement. In this paper, we address the problem of scheduling all movements in an express network at minimum cost. Our approach allows to impose restrictions on the number of arriving/departing movements at the hubs so that sufficient handling capacity is ensured. As the movement scheduling problem is complex, it is divided into two parts: one part concerns the movements between depots and hubs; the other part considers the movements between the hubs. We use a column generation approach and a local search algorithm to solve these two subproblems, respectively. Computational experiments show that by using this approach the total transportation costs are decreased.
Express service provider Movement scheduling Integer programming Column generation Local search
This is a preview of subscription content, log in to check access
Aarts EHL, Lenstra JK (2003) Local search in combinatorial optimization. Princeton University Press, PrincetonMATHGoogle Scholar
Armacost AP, Barnhart C, Ware KA (2002) Composite variable formulations for express shipment service network design. Transp Sci 36(1):1–20MATHCrossRefGoogle Scholar
Armacost AP, Barnhart C, Ware KA, Wilson AM (2004) UPS optimizes its air network. Interfaces 34(1):15–25CrossRefGoogle Scholar
Baltz A, Dubhashi D, Srivastav A, Tansini L, Werth S (2007) Probabilistic analysis for a multiple depot vehicle routing problem. Random Struct Algorithms 30(1–2):206–225MATHMathSciNetCrossRefGoogle Scholar
Barnhart C, Johnson EL, Nemhauser GL, Savelsbergh MWP, Vance PH (1998) Branch-and-price: column generation for solving huge integer programs. Oper Res 46(3):316–329MATHMathSciNetCrossRefGoogle Scholar