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

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Published:08 July 2020Publication History

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.

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References

  1. J. Karder, V. A. Hauder, A. Beham, K. Altendorfer, and M. Affenzeller. 2019. A New Solution Encoding for Simulation-Based Multi-Objective Workforce Qualification Optimization. In Proceedings of the 31st European Modeling and Simulation Symposium EMSS2019. Lisboa, Portugal, 8.Google ScholarGoogle Scholar
  2. Andreas Schober, Klaus Altendorfer, Johannes Karder, and Andreas Beham. 2019. Influence of Workforce Qualification on Service Level in a Flow Shop with two Lines. IFAC-PapersOnLine 52, 13 (2019), 553 -- 558. 9th IFAC Conference on Manufacturing Modelling, Management and Control MIM 2019. Google ScholarGoogle ScholarCross RefCross Ref

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  1. Multi-objective optimization for worker cross-training: the tri-objective case

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          cover image ACM Conferences
          GECCO '20: Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion
          July 2020
          1982 pages
          ISBN:9781450371278
          DOI:10.1145/3377929

          Copyright © 2020 Owner/Author

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          Association for Computing Machinery

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          Publication History

          • Published: 8 July 2020

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