弱次模化意味着本地化:受约束非次模块化函数最大化的局部搜索

IF 0.7 3区 数学 Q2 MATHEMATICS
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引用次数: 0

摘要

局部搜索算法通常用于解决运筹学和组合优化领域的各种问题。大多数关于受约束单调非次模化函数最大化的文献都基于贪婪策略,很少涉及局部搜索方法的设计。在本文中,我们用局部搜索算法探讨了在 p-matroid (p≥1) 约束下单调非次模化函数最大化的问题。我们指出,弱次模性意味着集合函数优化的可局部性,可用于为局部搜索算法提供可证明的近似保证。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Weak submodularity implies localizability: Local search for constrained non-submodular function maximization
Local search algorithms are commonly employed to address a variety of problems in the domain of operations research and combinatorial optimization. Most of the literature on the maximization of constrained monotone non-submodular functions is based on a greedy strategy, and few designs of local search approach are involved. In this paper, we explore the problem of maximizing a monotone non-submodular function under a p-matroid (p1) constraint with local search algorithms. And we indicate that weak submodularity implies localizability of set function optimization which can be used to offer provable approximation guarantees of local search algorithms.
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来源期刊
Discrete Mathematics
Discrete Mathematics 数学-数学
CiteScore
1.50
自引率
12.50%
发文量
424
审稿时长
6 months
期刊介绍: Discrete Mathematics provides a common forum for significant research in many areas of discrete mathematics and combinatorics. Among the fields covered by Discrete Mathematics are graph and hypergraph theory, enumeration, coding theory, block designs, the combinatorics of partially ordered sets, extremal set theory, matroid theory, algebraic combinatorics, discrete geometry, matrices, and discrete probability theory. Items in the journal include research articles (Contributions or Notes, depending on length) and survey/expository articles (Perspectives). Efforts are made to process the submission of Notes (short articles) quickly. The Perspectives section features expository articles accessible to a broad audience that cast new light or present unifying points of view on well-known or insufficiently-known topics.
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