Online cardinality constrained scheduling

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

Research output: Contribution to journalArticlepeer-review


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 languageEnglish
Pages (from-to)533-539
Number of pages7
JournalOperations Research Letters
Issue number5
StatePublished - Sep 2023

Bibliographical note

Funding Information:
L. Epstein and A. Levin were partially supported by GIF – the German-Israeli Foundation for Scientific Research and Development (grant number I-1366-407.6/2016 ). A. Lassota was supported by the Swiss National Science Foundation within the project Lattice algorithms and Integer Programming ( 200021_185030/1 ). A. Levin was also partially supported by grants from ISF – Israel Science Foundation (grant numbers 308/18 and 1467/22 ). M. Maack was partially supported by the German Research Foundation (DFG) within the Collaborative Research Centre “On-The-Fly Computing” under the project number 160364472 — SFB 901/3 .

Publisher Copyright:
© 2023 Elsevier B.V.


  • Competitive analysis
  • Load balancing
  • Online algorithms
  • Scheduling

ASJC Scopus subject areas

  • Software
  • Management Science and Operations Research
  • Industrial and Manufacturing Engineering
  • Applied Mathematics


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