Multi-objective optimization for worker cross-training: The tri-objective case

Publikation: Beitrag in Buch/Bericht/TagungsbandKonferenzbeitragBegutachtung

Abstract

Worker cross-training is a problem arising in many industries and companies that involve human work, since workers that possess multiple skills, i.e., a qualification profile, may be employed more flexible on a day-to-day basis. At the same time it can be assumed that these workers are also incur a higher personnel cost. It is therefore of high interest to a company to balance the available skills such that customer deadlines can be met in a cost-efficient way. In this work we extend a simulation-based optimization approach with a third objective and apply NSGA-II.

OriginalspracheEnglisch
TitelGECCO 2020 Companion - Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion
Herausgeber (Verlag)Association for Computing Machinery, Inc
Seiten257-258
Seitenumfang2
ISBN (elektronisch)9781450371278
DOIs
PublikationsstatusVeröffentlicht - 8 Jul 2020
Veranstaltung2020 Genetic and Evolutionary Computation Conference, GECCO 2020 - Cancun, Mexiko
Dauer: 8 Jul 202012 Jul 2020

Publikationsreihe

NameGECCO 2020 Companion - Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion

Konferenz

Konferenz2020 Genetic and Evolutionary Computation Conference, GECCO 2020
Land/GebietMexiko
OrtCancun
Zeitraum08.07.202012.07.2020

Fingerprint

Untersuchen Sie die Forschungsthemen von „Multi-objective optimization for worker cross-training: The tri-objective case“. Zusammen bilden sie einen einzigartigen Fingerprint.

Zitieren