An improved approximation algorithm for the subpath planning problem and its generalization

Hanna Sumita, Yuma Yonebayashi, Naonori Kakimura, Ken Ichi Kawarabayashi

研究成果: Conference contribution

4 被引用数 (Scopus)

抄録

This paper focuses on a generalization of the traveling salesman problem (TSP), called the subpath planning problem (SPP). Given 2n vertices and n independent edges on a metric space, we aim to find a shortest tour that contains all the edges. SPP is one of the fundamental problems in both artificial intelligence and robotics. Our main result is to design a 1.5-approximation algorithm that runs in polynomial time, improving the currently best approximation algorithm. The idea is direct use of techniques developed for TSP. In addition, we propose a generalization of SPP called the subgroup planning problem (SGPP). In this problem, we are given a set of disjoint groups of vertices, and we aim to find a shortest tour such that all the vertices in each group are traversed sequentially. We propose a 3-approximation algorithm for SGPP. We also conduct numerical experiments. Compared with previous algorithms, our algorithms improve the solution quality by more than 10% for large instances with more than 10,000 vertices.

本文言語English
ホスト出版物のタイトル26th International Joint Conference on Artificial Intelligence, IJCAI 2017
編集者Carles Sierra
出版社International Joint Conferences on Artificial Intelligence
ページ4412-4418
ページ数7
ISBN(電子版)9780999241103
DOI
出版ステータスPublished - 2017
イベント26th International Joint Conference on Artificial Intelligence, IJCAI 2017 - Melbourne, Australia
継続期間: 2017 8 192017 8 25

出版物シリーズ

名前IJCAI International Joint Conference on Artificial Intelligence
0
ISSN(印刷版)1045-0823

Other

Other26th International Joint Conference on Artificial Intelligence, IJCAI 2017
国/地域Australia
CityMelbourne
Period17/8/1917/8/25

ASJC Scopus subject areas

  • 人工知能

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