OPTIMAL ONLINE ALGORITHM FOR METRICAL TASK SYSTEMS.

Allan Borodin; Nathan Linial Nathan; Michael Saks

doi:10.1145/28395.28435

OPTIMAL ONLINE ALGORITHM FOR METRICAL TASK SYSTEMS.

Allan Borodin^*
, Nathan Linial Nathan
, Michael Saks

^*Corresponding author for this work

Research output: Contribution to journal › Conference article › peer-review

63 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 language	English
Pages (from-to)	373-382
Number of pages	10
Journal	Conference Proceedings of the Annual ACM Symposium on Theory of Computing
DOIs	https://doi.org/10.1145/28395.28435
State	Published - 1987
Externally published	Yes

Access to Document

10.1145/28395.28435

Cite this

@article{1656c26f09b54a9aba6f2dd0667aac42,

title = "OPTIMAL ONLINE ALGORITHM FOR METRICAL TASK SYSTEMS.",

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.",

author = "Allan Borodin and \{Linial Nathan\}, Nathan and Michael Saks",

year = "1987",

doi = "10.1145/28395.28435",

language = "אנגלית",

pages = "373--382",

journal = "Conference Proceedings of the Annual ACM Symposium on Theory of Computing",

issn = "0734-9025",

publisher = "Association for Computing Machinery",

}

TY - JOUR

T1 - OPTIMAL ONLINE ALGORITHM FOR METRICAL TASK SYSTEMS.

AU - Borodin, Allan

AU - Linial Nathan, Nathan

AU - Saks, Michael

PY - 1987

Y1 - 1987

N2 - 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.

AB - 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.

UR - https://www.scopus.com/pages/publications/0023545513

U2 - 10.1145/28395.28435

DO - 10.1145/28395.28435

M3 - ???researchoutput.researchoutputtypes.contributiontojournal.conferencearticle???

AN - SCOPUS:0023545513

SN - 0734-9025

SP - 373

EP - 382

JO - Conference Proceedings of the Annual ACM Symposium on Theory of Computing

JF - Conference Proceedings of the Annual ACM Symposium on Theory of Computing

ER -

OPTIMAL ONLINE ALGORITHM FOR METRICAL TASK SYSTEMS.

Abstract

Access to Document

Other files and links

Fingerprint

Cite this