OPTIMAL ONLINE ALGORITHM FOR METRICAL TASK SYSTEMS.

Allan Borodin, Nathan Linial Nathan, Michael Saks

Research output: Contribution to journalConference articlepeer-review

57 Scopus citations

Abstract

In practice, almost all dynamic systems require decisions to be made online, without full knowledge of their future impact on the system. We introduce a general model for the processing of sequences of tasks and develop a general online decision algorithm. We show that, for an important class of special cases, this algorithm is optimal among all online algorithms.

Original languageEnglish (US)
Pages (from-to)373-382
Number of pages10
JournalConference Proceedings of the Annual ACM Symposium on Theory of Computing
DOIs
StatePublished - 1987
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Software

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