On the parenthesisations of matrix chains: All are useful, few are essential

IF 0.9 4区 数学 Q4 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Francisco López, Lars Karlsson, Paolo Bientinesi
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引用次数: 0

Abstract

The product of a matrix chain consisting of n matrices can be computed in \(C_{n-1}\) (Catalan’s number) different ways, each identified by a distinct parenthesisation of the chain. The best algorithm to select a parenthesisation that minimises the cost runs in \(O(n \log n)\) time. Approximate algorithms run in O(n) time and find solutions that are guaranteed to be within a certain factor from optimal; the best factor is currently 1.155. In this article, we first prove two results that characterise different parenthesisations, and then use those results to improve on the best known approximation algorithms. Specifically, we show that (a) each parenthesisation is optimal somewhere in the problem domain, and (b) exactly \(n + 1\) parenthesisations are essential in the sense that the removal of any one of them causes an unbounded penalty for an infinite number of problem instances. By focusing on essential parenthesisations, we improve on the best known approximation algorithm and show that the approximation factor is at most 1.143.

关于矩阵链的括号:都是有用的,很少是必要的
由n个矩阵组成的矩阵链的乘积可以通过\(C_{n-1}\)(加泰罗尼亚数字)以不同的方式计算,每种方式都通过链的不同括号来标识。选择最小代价的圆括号的最佳算法运行时间为\(O(n \log n)\)。近似算法在O(n)时间内运行,并找到保证在最优的某个因子范围内的解;目前最好的汇率是1.155。在本文中,我们首先证明了表征不同括号的两个结果,然后使用这些结果来改进最著名的近似算法。具体来说,我们表明(a)每个括号在问题域的某个地方是最优的,并且(b) \(n + 1\)括号在某种意义上是必不可少的,因为删除它们中的任何一个都会对无限数量的问题实例造成无界惩罚。通过关注基本的括号,我们改进了最著名的近似算法,并表明近似因子最多为1.143。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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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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