Online cardinality constrained scheduling

Leah Epstein; Alexandra Lassota; Asaf Levin; Marten Maack; Lars Rohwedder

doi:10.1016/j.orl.2023.08.003

Online cardinality constrained scheduling

Leah Epstein^*, Alexandra Lassota, Asaf Levin, Marten Maack, Lars Rohwedder

^*Corresponding author for this work

Research output: Contribution to journal › Article › Academic › peer-review

Abstract

In online load balancing problems, jobs arrive over a list. Upon arrival of a job, the algorithm is required to assign it immediately and irrevocably to a machine. We consider such a makespan minimization problem with an additional cardinality constraint, i.e., at most k jobs may be assigned to each machine, where k is a parameter of the problem. We present both upper and lower bounds on the competitive ratio of online algorithms for this problem with identical machines.

Original language	English
Pages (from-to)	533-539
Number of pages	7
Journal	Operations Research Letters
Volume	51
Issue number	5
DOIs	https://doi.org/10.1016/j.orl.2023.08.003
Publication status	Published - 1 Sept 2023

Keywords

Competitive analysis
Load balancing
Online algorithms
Scheduling

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10.1016/j.orl.2023.08.003

Cite this

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abstract = "In online load balancing problems, jobs arrive over a list. Upon arrival of a job, the algorithm is required to assign it immediately and irrevocably to a machine. We consider such a makespan minimization problem with an additional cardinality constraint, i.e., at most k jobs may be assigned to each machine, where k is a parameter of the problem. We present both upper and lower bounds on the competitive ratio of online algorithms for this problem with identical machines.",

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AU - Lassota, Alexandra

AU - Levin, Asaf

AU - Maack, Marten

AU - Rohwedder, Lars

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PY - 2023/9/1

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N2 - In online load balancing problems, jobs arrive over a list. Upon arrival of a job, the algorithm is required to assign it immediately and irrevocably to a machine. We consider such a makespan minimization problem with an additional cardinality constraint, i.e., at most k jobs may be assigned to each machine, where k is a parameter of the problem. We present both upper and lower bounds on the competitive ratio of online algorithms for this problem with identical machines.

AB - In online load balancing problems, jobs arrive over a list. Upon arrival of a job, the algorithm is required to assign it immediately and irrevocably to a machine. We consider such a makespan minimization problem with an additional cardinality constraint, i.e., at most k jobs may be assigned to each machine, where k is a parameter of the problem. We present both upper and lower bounds on the competitive ratio of online algorithms for this problem with identical machines.

KW - Competitive analysis

KW - Load balancing

KW - Online algorithms

KW - Scheduling

U2 - 10.1016/j.orl.2023.08.003

DO - 10.1016/j.orl.2023.08.003

M3 - Article

SN - 0167-6377

VL - 51

SP - 533

EP - 539

JO - Operations Research Letters

JF - Operations Research Letters

IS - 5

ER -

Online cardinality constrained scheduling

Abstract

Keywords

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