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Design of cellular networks with diversity and capacity constraints

机译:具有多样性和容量限制的蜂窝网络设计

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This paper presents three mathematical models for network design of cellular networks. The models reflect varying degrees of complexity. Model 1 is a 1-period fixed-link capacity model. Three heuristics are used for solving this problem. All the heuristics first use linear programming relaxations to yield the near-optimal integer solution, then use clever rounding-schemes to find the final solution. The three heuristics are compared with an integer branch-and-bound algorithm to show the efficacy of the heuristics and the speed with which they achieve their solution. The first heuristic is the best. An appendix presents a detailed algorithmic description of the first heuristic. Model 2 allows the capacities of the links to vary. This is a much more difficult mathematical programming problem, yet certain features of the problem reveal valuable characteristics of the linear programming relaxations. Two heuristics are generated; the first heuristic is superior to the second. The heuristics are compared with an optimal branch-and-bound algorithm. Model 3 presents a multi-period demand problem. This is a very complex problem and, while no heuristics are developed and no computational experiments are shown, the structure of the final problem is similar to models 1 and 2; thus linear programming relaxations should be a viable strategy for its solution.
机译:本文提出了用于蜂窝网络的网络设计的三个数学模型。这些模型反映了不同程度的复杂性。模型1是1周期固定链路容量模型。三种启发式方法用于解决此问题。所有试探法首先使用线性规划松弛来产生接近最佳的整数解,然后使用聪明的舍入方案来找到最终解。将这三种启发式算法与整数分支定界算法进行比较,以显示启发式算法的功效以及它们实现解决方案的速度。第一次启发式是最好的。附录提供了对第一种启发式算法的详细算法描述。模型2允许链接的容量变化。这是一个难度更大的数学编程问题,但是该问题的某些特征揭示了线性规划松弛的有价值的特征。产生两种启发式方法;第一种启发式方法优于第二种。将启发式方法与最佳分支定界算法进行比较。模型3提出了一个多期间需求问题。这是一个非常复杂的问题,尽管未开发启发式方法且未显示任何计算实验,但最终问题的结构与模型1和2相似。因此,线性规划松弛应该是其解决方案的可行策略。

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