Better approximating SONET k-edge partition for small capacity k

IF 0.9 4区 数学 Q4 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Junhui Ye, Huihuang Jiang, Guangting Chen, Yong Chen, Guohui Lin, An Zhang
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引用次数: 0

Abstract

We study the SONET edge partition problem that models telecommunication network design to partition the edge set of a given graph into several edge-disjoint subgraphs, such that each subgraph has size no greater than a given capacity k and the sum of the orders of these subgraphs is minimized. The problem is NP-hard when \(k \ge 3\) and admits an \(O(\log k)\)-approximation algorithm. For small capacity \(k = 3, 4, 5\), by observing that some subgraph structures are more favorable than the others, we propose modifications to existing algorithms and design novel amortization schemes to prove their improved performance. Our algorithmic results include a \(\frac{4}{3}\)-approximation for \(k = 3\), improving the previous best \(\frac{13}{9}\)-approximation, a \(\frac{4}{3}\)-approximation for \(k = 4\), improving the previous best \((\frac{4}{3} + \epsilon )\)-approximation, and a \(\frac{3}{2}\)-approximation for \(k = 5\), improving the previous best \(\frac{5}{3}\)-approximation. Besides these improved algorithms, our main contribution is the amortization scheme design, which can be helpful for similar algorithms and problems.

对小容量k更好地逼近SONET k边划分
研究了电信网络设计的SONET边划分问题,将给定图的边集划分为几个边不相交的子图,使得每个子图的大小不大于给定容量k,并且这些子图的阶数之和最小。当\(k \ge 3\)和承认\(O(\log k)\)近似算法时,问题是np困难的。对于小容量\(k = 3, 4, 5\),通过观察一些子图结构比其他子图结构更有利,我们提出了对现有算法的修改,并设计了新的摊销方案来证明其改进的性能。我们的算法结果包括\(k = 3\)的\(\frac{4}{3}\)近似,改进了之前的最佳近似\(\frac{13}{9}\); \(k = 4\)的\(\frac{4}{3}\)近似,改进了之前的最佳近似\((\frac{4}{3} + \epsilon )\); \(k = 5\)的\(\frac{3}{2}\)近似,改进了之前的最佳近似\(\frac{5}{3}\)。除了这些改进的算法,我们的主要贡献是摊销方案的设计,可以帮助类似的算法和问题。
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来源期刊
Journal of Combinatorial Optimization
Journal of Combinatorial Optimization 数学-计算机:跨学科应用
CiteScore
2.00
自引率
10.00%
发文量
83
审稿时长
6 months
期刊介绍: The objective of Journal of Combinatorial Optimization is to advance and promote the theory and applications of combinatorial optimization, which is an area of research at the intersection of applied mathematics, computer science, and operations research and which overlaps with many other areas such as computation complexity, computational biology, VLSI design, communication networks, and management science. It includes complexity analysis and algorithm design for combinatorial optimization problems, numerical experiments and problem discovery with applications in science and engineering. The Journal of Combinatorial Optimization publishes refereed papers dealing with all theoretical, computational and applied aspects of combinatorial optimization. It also publishes reviews of appropriate books and special issues of journals.
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