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Improved Randomized Algorithm for k-Submodular Function Maximization
SIAM Journal on Discrete Mathematics ( IF 0.8 ) Pub Date : 2021-01-05 , DOI: 10.1137/19m1277692
Hiroki Oshima

SIAM Journal on Discrete Mathematics, Volume 35, Issue 1, Page 1-22, January 2021.
Submodularity is one of the most important properties in combinatorial optimization, and $k$-submodularity is a generalization of submodularity. Maximization of a $k$-submodular function requires an exponential number of value oracle queries, and approximation algorithms have been studied. For unconstrained $k$-submodular maximization, Iwata, Tanigawa, and Yoshida, [Improved approximation algorithms for $k$-submodular function maximization, in Proceedings of the Twenty-Seventh Annual ACM-SIAM Symposium on Discrete Algorithms, SIAM, Philadelphia, 2016, pp. 404--413] gave a randomized $k/(2k-1)$-approximation algorithm for monotone functions and a randomized 1/2-approximation algorithm for nonmonotone functions. In this paper, we present improved randomized algorithms for nonmonotone functions. Our algorithm gives a $\frac{k^2+1}{2k^2+1}$-approximation for $k\geq 3$. We also give a randomized $\frac{\sqrt{17}-3}{2}$-approximation algorithm for $k=3$. We use the same framework used in Iwata, Tanigawa, and Yoshida, [Improved approximation algorithms for $k$-submodular function maximization, in Proceedings of the Twenty-Seventh Annual ACM-SIAM Symposium on Discrete Algorithms, SIAM, Philadelphia, 2016, pp. 404--413] and Ward and Živný [ACM Trans. Algorithms, 12 (2016), pp. 46:1--47:26] with different probabilities.


中文翻译:

k-子模函数最大化的改进随机算法

SIAM 离散数学杂志,第 35 卷,第 1 期,第 1-22 页,2021 年 1 月。
子模块性是组合优化中最重要的属性之一,$k$-submodularity 是子模块性的推广。$k$-submodular 函数的最大化需要指数数量的值 oracle 查询,并且已经研究了近似算法。对于无约束的 $k$-submodular 最大化,Iwata、Tanigawa 和 Yoshida,[改进的 $k$-submodular 函数最大化近似算法,在第 27 届年度 ACM-SIAM 离散算法研讨会论文集,SIAM,费城,2016 年, pp. 404--413] 给出了用于单调函数的随机 $k/(2k-1)$-近似算法和用于非单调函数的随机 1/2-近似算法。在本文中,我们提出了非单调函数的改进随机算法。我们的算法给出了 $k\geq 3$ 的 $\frac{k^2+1}{2k^2+1}$-近似值。我们还给出了 $k=3$ 的随机 $\frac{\sqrt{17}-3}{2}$-近似算法。我们使用在 Iwata、Tanigawa 和 Yoshida 中使用的相同框架,[改进的 $k$-submodular 函数最大化近似算法,在第 27 届年度 ACM-SIAM 离散算法研讨会论文集,SIAM,费城,2016 年,pp . . 404--413] 和 Ward 和 Živný [ACM Trans. Algorithms, 12 (2016), pp. 46:1--47:26] 具有不同的概率。SIAM, Philadelphia, 2016, pp. 404--413] and Ward and Živný [ACM Trans. Algorithms, 12 (2016), pp. 46:1--47:26] 具有不同的概率。SIAM, Philadelphia, 2016, pp. 404--413] and Ward and Živný [ACM Trans. Algorithms, 12 (2016), pp. 46:1--47:26] 具有不同的概率。
更新日期:2021-01-05
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