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Bibliographic Record
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- Material Type
- 文書・図像類
- Author/Editor
- 長谷川, 駿Hasegawa, Shun伊東, 利哉Itoh, Toshiya
- Author Heading
- Publication Date
- 2015-06
- Publication Date (W3CDTF)
- 2015-06
- Text Language Code
- eng
- Target Audience
- 一般
- Note (General)
- Tiedemann, et al. [Proc. of WALCOM, LNCS 8973, 2015, pp.210-221] defined multi-objective online problems and the competitive analysis for multi-objective online problems and showed that (1) with respect to the worst component competitive analysis, the online algorithm reservation price policy RPP-HIGH is best possible for the multi-objective time series search problem, (2) with respect to the arithmetic mean component competitive analysis, the online algorithm RPP-MULT is best possible for the bi-objective time series search problem; (3) with respect to the geometric mean component competitive analysis, the online algorithm RPP-MULT is best possible for the bi-objective time series search problem. In this paper, we present a simple~online algorithm Balanced Price Policy $BPP_{k}$ for the multi-objective ($k$-objective) time series search problem, and show that the algorithm $BPP_{k}$ is best possible with respect to any measure of the competitive analysis. In addition, we derive exact values of the competitive ratio for the multi-objective time series search problem with respect to the worst component, the arithmetic mean component, and the geometric mean component competitive analysis.identifier:oai:t2r2.star.titech.ac.jp:50279705
- Data Provider (Database)
- 国立情報学研究所 : 学術機関リポジトリデータベース（IRDB）（機関リポジトリ）