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Express package carrier networks have large numbers of heavily‐interconnected and tightly‐constrained resources, making the planning process difficult. A decision made in one area of the network can impact virtually any other area as well. Mathematical programming therefore seems like a logical approach to solving such problems, taking into account all of these interactions. The tight time windows and nonlinear cost functions of these systems, however, often make traditional approaches such as multicommodity flow formulations intractable. This is due to both the large number of constraints and the weakness of the linear programming (LP) relaxations arising in these formulations. To overcome these obstacles, we propose a model in which variables represent combinations of loads and their corresponding routings, rather than assigning individual loads to individual arcs in the network. In doing so, we incorporate much of the problem complexity implicitly within the variable definition, rather than explicitly within the constraints. This approach enables us to linearize the cost structure, strengthen the LP relaxation of the formulation, and drastically reduce the number of constraints. In addition, it greatly facilitates the inclusion of other stages of the (typically decomposed) planning process. We show how the use of templates, in place of traditional delayed column generation, allows us to identify promising candidate variables, ensuring high‐quality solutions in reasonable run times while also enabling the inclusion of additional operational considerations that would be difficult if not impossible to capture in a traditional approach. Computational results are presented using data from a major international package carrier. © 2008 Wiley Periodicals, Inc. Naval Research Logistics, 2008 相似文献
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雷达目标宽带全极化测量在雷达成像、目标识别等领域有着重要应用,为此,基于正交频率分集思想,设计了一种用于宽带全极化瞬时测量的矢量信号波形;给出发射信号模型和回波信号模型,利用该波形的单个脉冲回波,可以获取测量带宽内多频点全极化数据,再经逆离散傅立叶变换后可以得到目标的全极化一维距离像;最后,用仿真数据和实测数据进行仿真实验,验证了该方法的有效性. 相似文献
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