A Framework for the complexity of high multiplicity scheduling problems

N. Brauner; Y. Crama; A. Grigoriev; Joris van de Klundert

doi:10.1007/s10878-005-1414-7

A Framework for the complexity of high multiplicity scheduling problems

N. Brauner^*, Y. Crama, A. Grigoriev, Joris van de Klundert

^*Corresponding author for this work

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

Abstract

The purpose of this note is to propose a complexity framework for the analysis of high multiplicity scheduling problems. Part of this framework relies on earlier work aiming at the definition of output-sensitive complexity measures for the analysis of algorithms which produce “large” outputs. However, different classes emerge according as we look at schedules as sets of starting times, or as related single-valued mappings.

Original language	English
Pages (from-to)	313-323
Number of pages	11
Journal	Journal of Combinatorial Optimization
Volume	9
Issue number	3
DOIs	https://doi.org/10.1007/s10878-005-1414-7
Publication status	Published - 1 Jan 2005

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10.1007/s10878-005-1414-7

Cite this

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title = "A Framework for the complexity of high multiplicity scheduling problems",

abstract = "The purpose of this note is to propose a complexity framework for the analysis of high multiplicity scheduling problems. Part of this framework relies on earlier work aiming at the definition of output-sensitive complexity measures for the analysis of algorithms which produce “large” outputs. However, different classes emerge according as we look at schedules as sets of starting times, or as related single-valued mappings.",

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AB - The purpose of this note is to propose a complexity framework for the analysis of high multiplicity scheduling problems. Part of this framework relies on earlier work aiming at the definition of output-sensitive complexity measures for the analysis of algorithms which produce “large” outputs. However, different classes emerge according as we look at schedules as sets of starting times, or as related single-valued mappings.

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