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Exact solutions of rectangular partitions via integer programming

机译:通过整数编程的矩形分区的精确解

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Given a rectangle R in the plane and a finite set P of points in its interior, consider the partitions of the surface of R into smaller rectangles. A partition is feasible with respect to P if each point in P lie on the boundary of some rectangle of the partition. The length of a partition is computed as the sum of the lengths of the line segments defining the boundary of its rectangles. The goal is to find a feasible partition with minimum length. This problem, denoted by RGP, belongs to NP-hard and has application in VLSI design. In this paper we investigate how to obtain exact solutions for the RGP. We introduce two different Integer Programming formulations and carry out a theoretical study to evaluate and compare the strength of their bounds. Computational experiments are reported for Branch-and-Cut and Branch-and Price algorithms we have implemented for the first and the second formulation, respectively. Randomly generated instances with |P| ≤ 200 are solved exactly. The tests indicate that the size of the instances solved with our algorithms decrease by an order of magnitude in the absence of corectilinear points in P, a special case of RGP whose complexity is still open.
机译:给定平面中的矩形R和其内部的有限点集P,请考虑将R的表面划分为较小的矩形。如果P中的每个点都位于分区的某个矩形的边界上,则对于P而言,分区是可行的。分区的长度计算为定义矩形边界的线段长度的总和。目标是找到一个最小长度的可行分区。这个问题用RGP表示,属于NP难题,已在VLSI设计中得到应用。在本文中,我们研究了如何为RGP获得精确的解决方案。我们介绍了两种不同的Integer编程公式,并进行了理论研究以评估和比较其边界的强度。报告了分别针对第一种和第二种配方实施的分支剪切法和分支价格法的计算实验。 | P |随机生成的实例≤200可以精确求解。测试表明,在P中不存在核心直线点的情况下,用我们的算法求解的实例大小减小了一个数量级,这是RGP的一种特殊情况,其复杂性仍然存在。

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