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

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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.

Original languageEnglish
Title of host publicationGECCO 2020 Companion - Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion
PublisherAssociation for Computing Machinery, Inc
Pages257-258
Number of pages2
ISBN (Electronic)9781450371278
DOIs
Publication statusPublished - 8 Jul 2020
Event2020 Genetic and Evolutionary Computation Conference, GECCO 2020 - Cancun, Mexico
Duration: 8 Jul 202012 Jul 2020

Publication series

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

Conference

Conference2020 Genetic and Evolutionary Computation Conference, GECCO 2020
CountryMexico
CityCancun
Period08.07.202012.07.2020

Keywords

  • Multi-objective optimization
  • Simulation-based optimization
  • Skill management

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