Numerous communication networks are emerging to serve the various demands and improve the quality of service. Heterogeneous users have different requirements on quality metrics such as delay and service efficiency. Besides, the networks are equipped with different types and amounts of resources, and how to efficiently optimize the usage of such limited resources to serve more users is the key issue for communication networks. One powerful mathematical optimization mechanism to solve the above issue is column generation (CG), which can deal with the optimization problems with complicating constraints and block angular structures. In this paper, we first review the preliminaries of CG. Further, the branch-and-price (BP) algorithm is elaborated, which is designed by embedding CG into the branch-and-bound scheme to efficiently obtain the optimal solution. The applications of CG and BP in various communication networks are then provided, such as space-air-ground networks and device-to-device networks. In short, our goal is to help readers refine the applications of the CG optimization tool in terms of problem formulation and solution. We also discuss the possible challenges and prospective directions when applying CG in the communication networks.
翻译:许多通信网络正在涌现,以满足各种需求并改进服务质量。不同种类的用户对诸如延迟和服务效率等质量衡量标准有不同的要求。此外,网络配备了不同类型和数量的资源,以及如何有效地优化利用这种有限的资源为更多的用户服务是通信网络的关键问题。解决上述问题的强大数学优化机制是生成柱子,它可以处理复杂制约和阻塞角结构的优化问题。我们本文件首先审查CG的初步情况。此外,还详细制定了分支和价格(BP)算法,其设计方法是将CG嵌入分支和约束计划,以有效获得最佳解决方案。然后提供CG和BP在各种通信网络中的应用,如空间-空地网络和装置-装置-装置网络。简而言之,我们的目标是帮助读者改进CG优化工具在问题设计和解决方案方面的应用。我们还讨论了通信网络应用CG时可能遇到的挑战和今后的方向。