容量最小-最大相关聚类问题的逼近算法

IF 1.1 4区 管理学 Q4 OPERATIONS RESEARCH & MANAGEMENT SCIENCE
S. Ji, Jun Li, Zijun Wu, Yicheng Xu
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引用次数: 0

摘要

在本文中,我们提出了一个所谓的有能力的最小-最大相关聚类模型,它是最小-最大相关聚类问题的自然变体。作为我们的主要贡献,我们提出了一个整数规划及其完整性缺口分析所提出的模型。此外,我们提供了两种近似算法,一种是双准则近似算法,另一种是基于lp舍入技术的近似算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Approximation Algorithms for the Capacitated Min–Max Correlation Clustering Problem
In this paper, we propose a so-called capacitated min–max correlation clustering model, a natural variant of the min–max correlation clustering problem. As our main contribution, we present an integer programming and its integrality gap analysis for the proposed model. Furthermore, we provide two approximation algorithms for the model, one of which is a bi-criteria approximation algorithm and the other is based on LP-rounding technique.
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来源期刊
Asia-Pacific Journal of Operational Research
Asia-Pacific Journal of Operational Research 管理科学-运筹学与管理科学
CiteScore
2.00
自引率
14.30%
发文量
44
审稿时长
14.2 months
期刊介绍: The Asia-Pacific Journal of Operational Research (APJOR) provides a forum for practitioners, academics and researchers in Operational Research and related fields, within and beyond the Asia-Pacific region. APJOR will place submissions in one of the following categories: General, Theoretical, OR Practice, Reviewer Survey, OR Education, and Communications (including short articles and letters). Theoretical papers should carry significant methodological developments. Emphasis is on originality, quality and importance, with particular emphasis given to the practical significance of the results. Practical papers, illustrating the application of Operation Research, are of special interest.
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