Fractionally Subadditive Maximization under an Incremental Knapsack Constraint with Applications to Incremental Flows

IF 0.9 3区 数学 Q2 MATHEMATICS
Yann Disser, Max Klimm, Annette Lutz, David Weckbecker
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引用次数: 0

Abstract

SIAM Journal on Discrete Mathematics, Volume 38, Issue 1, Page 764-789, March 2024.
Abstract. We consider the problem of maximizing a fractionally subadditive function under an increasing knapsack constraint. An incremental solution to this problem is given by an order in which to include the elements of the ground set, and the competitive ratio of an incremental solution is defined by the worst ratio over all capacities relative to an optimum solution of the corresponding capacity. We present an algorithm that finds an incremental solution of competitive ratio at most [math], under the assumption that the values of singleton sets are in the range [math], and we give a lower bound of [math] on the attainable competitive ratio. In addition, we establish that our framework captures potential-based flows between two vertices, and we give a lower bound of [math] and an upper bound of [math] for the incremental maximization of classical flows with capacities in [math] which is tight for the unit capacity case.
增量包约束条件下的分数次增量最大化及其在增量流量中的应用
SIAM 离散数学杂志》,第 38 卷,第 1 期,第 764-789 页,2024 年 3 月。 摘要。我们考虑的问题是,在一个递增的包约束条件下,最大化一个分数次正函数。该问题的增量解由包含地面集元素的顺序给出,增量解的竞争率由所有容量相对于相应容量最优解的最差比率定义。我们提出了一种算法,在假设单子集的值在[math]范围内的情况下,它能找到竞争比最多为[math]的增量解,我们还给出了可达到的竞争比的下限[math]。此外,我们还确定了我们的框架可以捕捉到两个顶点之间基于势的流量,并给出了容量在 [math] 范围内的经典流量增量最大化的 [math] 下限和 [math] 上限,这对于单位容量情况来说是严密的。
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来源期刊
CiteScore
1.90
自引率
0.00%
发文量
124
审稿时长
4-8 weeks
期刊介绍: SIAM Journal on Discrete Mathematics (SIDMA) publishes research papers of exceptional quality in pure and applied discrete mathematics, broadly interpreted. The journal''s focus is primarily theoretical rather than empirical, but the editors welcome papers that evolve from or have potential application to real-world problems. Submissions must be clearly written and make a significant contribution. Topics include but are not limited to: properties of and extremal problems for discrete structures combinatorial optimization, including approximation algorithms algebraic and enumerative combinatorics coding and information theory additive, analytic combinatorics and number theory combinatorial matrix theory and spectral graph theory design and analysis of algorithms for discrete structures discrete problems in computational complexity discrete and computational geometry discrete methods in computational biology, and bioinformatics probabilistic methods and randomized algorithms.
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