OPTIMAL ONLINE ALGORITHM FOR METRICAL TASK SYSTEMS.

Allan Borodin, Nathan Linial Nathan, Michael Saks

Research output: Contribution to journalConference article

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
StatePublished - Dec 1 1987
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Software

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