IMPROVING APPROXIMATION RATIOS FOR THE CLUSTERED TRAVELING SALESMAN PROBLEM

Masamune Kawasaki, Kenjiro Takazawa
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引用次数: 4

Abstract

The clustered traveling salesman problem (CTSP) is a generalization of the traveling salesman problem (TSP) in which the set of cities is divided into clusters and the salesman must consecutively visit the cities of each cluster. It is well known that TSP is NP-hard, and hence CTSP is NP-hard as well. Guttmann-Beck et al. (2000) designed approximation algorithms for several variants of CTSP by decomposing it into subproblems including the traveling salesman path problem (TSPP). In this paper, we improve approximation ratios by applying a recent improved approximation algorithm for TSPP by Zenklusen (2019).
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改进了聚类旅行推销员问题的近似比
集群旅行推销员问题(CTSP)是旅行推销员问题的推广,其中城市集被划分为集群,推销员必须连续访问每个集群的城市。众所周知,TSP是NP难的,因此CTSP也是NP难的。Guttmann-Beck等人(2000)通过将CTSP分解为包括旅行商路径问题(TSPP)在内的子问题,为CTSP的几种变体设计了近似算法。在本文中,我们通过应用Zenklusen(2019)最近改进的TSPP近似算法来提高近似率。
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
Journal of the Operations Research Society of Japan
Journal of the Operations Research Society of Japan 管理科学-运筹学与管理科学
CiteScore
0.70
自引率
0.00%
发文量
12
审稿时长
12 months
期刊介绍: The journal publishes original work and quality reviews in the field of operations research and management science to OR practitioners and researchers in two substantive categories: operations research methods; applications and practices of operations research in industry, public sector, and all areas of science and engineering.
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