Unranking combinations using gradient-based optimization

研究成果: Conference contribution

1 被引用数 (Scopus)

抄録

Combinations of m out of n are ubiquitous to model a wide class of combinatorial problems. For an ordered sequence of combinations, the unranking function generates the combination associated to an integer number in the ordered sequence. In this paper, we present a new method for unranking combinations by using a gradient-based optimization approach. Exhaustive experiments within computable allowable limits confirmed the feasibility and efficiency of our proposed approach. Particularly, our algorithmic realization aided by a Graphics Processing Unit (GPU) was able to generate arbitrary combinations within 0.571 seconds and 8 iterations in the worst case scenario, for n up to 1000 and m up to 100. Also, the performance and efficiency to generate combinations are independent of n, being meritorious when n is very large compared to m, or when n is time-varying. Furthermore, the number of required iterations to generate the combinations by the gradient-based optimization decreases with m in average, implying the attractive scalability in terms of m. Our proposed approach offers the building blocks to enable the succinct modeling and the efficient optimization of combinatorial structures.

本文言語English
ホスト出版物のタイトルProceedings - 2018 IEEE 30th International Conference on Tools with Artificial Intelligence, ICTAI 2018
出版社IEEE Computer Society
ページ579-586
ページ数8
ISBN(電子版)9781538674499
DOI
出版ステータスPublished - 2018 12 13
イベント30th International Conference on Tools with Artificial Intelligence, ICTAI 2018 - Volos, Greece
継続期間: 2018 11 52018 11 7

出版物シリーズ

名前Proceedings - International Conference on Tools with Artificial Intelligence, ICTAI
2018-November
ISSN(印刷版)1082-3409

Other

Other30th International Conference on Tools with Artificial Intelligence, ICTAI 2018
国/地域Greece
CityVolos
Period18/11/518/11/7

ASJC Scopus subject areas

  • ソフトウェア
  • 人工知能
  • コンピュータ サイエンスの応用

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