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Approximation algorithms for MAX-3-CUT and other problems via complex semidefinite programming

机译:通过复杂的半定编程对MAX-3-CUT和其他问题的近似算法

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摘要

A number of recent papers on approximation algorithms have used the square roots of unity, -1 and 1, to represent binary decision variables for problems in combinatorial optimization, and have relaxed these to unit vectors in real space using semidefinite programming in order to obtain near optimum solutions to these problems. In this paper, we consider using the cube roots of unity, 1, e(i2pi/3), and e(i4pi/3), to represent ternary decision variables for problems in combinatorial optimization. Here the natural relaxation is that of unit vectors in complex space. We use an extension of semidefinite programming to complex space to solve the natural relaxation, and use a natural extension of the random hyperplane technique introduced by the authors in Goemans and Williamson (J. ACM 42 (1995) 1115-1145) to obtain near-optimum solutions to the problems. In particular, we consider the problem of maximizing the total weight of satisfied equations x(u) - x(v) drop c (mod 3) and inequations x - x(v) not equivalent to c (mod 3), where x(u) epsilon {0, 1, 2} for all u. This problem can be used to model the MAx-3-CUT problem and a directed variant we call MAX-3-DICUT. For the general problem, we obtain a 0.793733-approximation algorithm. If the instance contains only inequations (as it does for MAX-3-CUT), we obtain a performance guarantee of (7)/(12) + (3)/(4pi2) arccos(2)(- 1/4) - epsilon>0.836008. This compares with proven performance guarantees of 0.800217 for MAX-3-CUT (by Frieze and Jerrum (Algorithmica 18 (1997) 67-81) and 1 + 10(-8) for the general problem (by Andersson et al. (J. Algorithms 3 39 (2001) 162-204)). It matches the guarantee of 0.836008 for MAX-3-CUT found independently by de Klerk et al. (On approximate graph colouring and Max-k-Cut algorithms based on the 9-function, Manuscript, October 2000). We show that all these algorithms are in fact equivalent in the case of MAX-3CUT, and that our algorithm is the same as that of Andersson et al. in the more general case. (C) 2003 Elsevier Inc. All rights reserved. [References: 30]
机译:关于逼近算法的许多最新论文都使用单位为-1和1的平方根来表示组合优化中问题的二进制决策变量,并使用半定规划将它们简化为实际空间中的单位矢量,从而获得近似值。这些问题的最佳解决方案。在本文中,我们考虑使用单位为1,e(i2pi / 3)和e(i4pi / 3)的立方根来表示组合优化问题的三元决策变量。这里的自然弛豫是复杂空间中单位矢量的自然弛豫。我们使用半定规划的扩展到复杂的空间来解决自然松弛,并使用作者在Goemans和Williamson(J. ACM 42(1995)1115-1145)中引入的随机超平面技术的自然扩展来获得接近-问题的最佳解决方案。特别地,我们考虑最大化满足方程x(u)-x(v)下降c(mod 3)和不等式x-x(v)的总权重不等于c(mod 3)的问题,其中x( u)所有u的epsilon {0,1,2}。此问题可用于为MAx-3-CUT问题和我们称为MAX-3-DICUT的有向变量建模。对于一般问题,我们获得了0.793733的近似算法。如果实例仅包含不等式(与MAX-3-CUT一样),则我们可以获得(7)/(12)+(3)/(4pi2)arccos(2)(-1/4)- epsilon> 0.836008。相比之下,对于MAX-3-CUT(Frieze和Jerrum(Algorithmica 18(1997)67-81)和一般问题的1 + 10(-8)(Andersson等人(J.算法3 39(2001)162-204)),它与de Klerk等人独立发现的MAX-3-CUT的0.836008保证相匹配(基于9函数的近似图着色和Max-k-Cut算法) (《手稿》,2000年10月),我们证明在MAX-3CUT情况下,所有这些算法实际上都是等效的,在更一般的情况下,我们的算法与Andersson等人的算法是相同的(C)2003 Elsevier Inc.保留所有权利[引用:30]

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