Generalized minimum 0-extension problem and discrete convexity

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS
Martin Dvorak, Vladimir Kolmogorov
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引用次数: 0

Abstract

Given a fixed finite metric space \((V,\mu )\), the minimum 0-extension problem, denoted as \(\mathtt{0\hbox {-}Ext}[{\mu }]\), is equivalent to the following optimization problem: minimize function of the form \(\min \nolimits _{x\in V^n} \sum _i f_i(x_i) + \sum _{ij} c_{ij}\hspace{0.5pt}\mu (x_i,x_j)\) where \(f_i:V\rightarrow \mathbb {R}\) are functions given by \(f_i(x_i)=\sum _{v\in V} c_{vi}\hspace{0.5pt}\mu (x_i,v)\) and \(c_{ij},c_{vi}\) are given nonnegative costs. The computational complexity of \(\mathtt{0\hbox {-}Ext}[{\mu }]\) has been recently established by Karzanov and by Hirai: if metric \(\mu \) is orientable modular then \(\mathtt{0\hbox {-}Ext}[{\mu }]\) can be solved in polynomial time, otherwise \(\mathtt{0\hbox {-}Ext}[{\mu }]\) is NP-hard. To prove the tractability part, Hirai developed a theory of discrete convex functions on orientable modular graphs generalizing several known classes of functions in discrete convex analysis, such as \(L^\natural \)-convex functions. We consider a more general version of the problem in which unary functions \(f_i(x_i)\) can additionally have terms of the form \(c_{uv;i}\hspace{0.5pt}\mu (x_i,\{u,v\})\) for \(\{u,\!\hspace{0.5pt}\hspace{0.5pt}v\}\in F\), where set \(F\subseteq \left( {\begin{array}{c}V\\ 2\end{array}}\right) \) is fixed. We extend the complexity classification above by providing an explicit condition on \((\mu ,F)\) for the problem to be tractable. In order to prove the tractability part, we generalize Hirai’s theory and define a larger class of discrete convex functions. It covers, in particular, another well-known class of functions, namely submodular functions on an integer lattice. Finally, we improve the complexity of Hirai’s algorithm for solving \(\mathtt{0\hbox {-}Ext}[{\mu }]\) on orientable modular graphs.

Abstract Image

广义最小 0-扩展问题和离散凸性
给定一个固定的有限度量空间((V,\mu )),最小0-扩展问题,表示为((\mathtt{0\hbox {-}Ext}[{\mu }]\),等价于下面的优化问题:最小化函数的形式((\min \nolimits _{x\in V^n}\sum _i f_i(x_i) + \sum _{ij} c_{ij}\hspace{0.5pt}\mu (x_i,x_j)\) 其中 \(f_i:V\rightarrow \mathbb {R}\) 是由\(f_i(x_i)=\sum _{v\in V} c_{vi}\hspace{0.5pt}\mu (x_i,v)\) 和 \(c_{ij},c_{vi}\) 都是非负成本。Karzanov 和 Hirai 最近确定了 \(\mathtt{0\hbox {-}Ext}[{\mu }]\)的计算复杂度:如果度量 \(\mu \) 是可定向的模态,那么 \(\mathtt{0\hbox {-}Ext}[{\mu }]\)可以在多项式时间内求解,否则 \(\mathtt{0\hbox {-}Ext}[{\mu }]\)就是 NP 难的。为了证明可操作性部分,Hirai 发展了可定向模块图上的离散凸函数理论,概括了离散凸分析中的几类已知函数,如 \(L^\natural \)-凸函数。我们考虑了问题的一个更一般的版本,其中一元函数 \(f_i(x_i)\)可以额外具有形式为 \(c_{uv;i}\hspace{0.5pt}\mu (x_i,\{u,v\})\) for \(\{u,\!\hspace{0.5pt}\hspace{0.5pt}v\}\in F\), 其中集合 \(F\subseteq \left( {\begin{array}{c}V\\ 2\end{array}\right) \) 是固定的。我们扩展了上面的复杂性分类,为问题的可操作性提供了一个明确的条件((\mu ,F)\)。为了证明可处理性,我们推广了平井的理论,定义了一类更大的离散凸函数。它尤其涵盖了另一类众所周知的函数,即整数网格上的子模函数。最后,我们改进了平井算法求解可定向模块图上的\(\mathtt{0\hbox {-}Ext}[{\mu }]\)的复杂性。
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
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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