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Calibrating cross-training to meet demand mix variation and employee absence

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  • Olivella, Jordi
  • Nembhard, David

Abstract

We address the problem of determining the cross-training that a work team needs in order to cope with demand mix variation and absences. We consider the case in which all workers can be trained on all tasks, the workforce is a resource that determines the capacity and a complete forecasting of demand is not available. The demand mix variation that the organization wants to be able to cope with is fixed by establishing a maximum time to devote to each product. We contend that this approach is straightforward, has managerial practicality and can be applied to a broad range of practical scenarios. It is required that the demand mix variation be met, even if there are a certain level of absences. To numerically solve the mathematical problem, a constraint-based selection procedure is developed, which we term CODEMI. We provide illustrated examples demonstrating solution quality for the approximation, and we report on an illustrative set of computational cases.

Suggested Citation

  • Olivella, Jordi & Nembhard, David, 2016. "Calibrating cross-training to meet demand mix variation and employee absence," European Journal of Operational Research, Elsevier, vol. 248(2), pages 462-472.
    • Handle: RePEc:eee:ejores:v:248:y:2016:i:2:p:462-472
    DOI: 10.1016/j.ejor.2015.07.036
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    Cited by:

    1. Ingels, Jonas & Maenhout, Broos, 2019. "Optimised buffer allocation to construct stable personnel shift rosters," Omega, Elsevier, vol. 82(C), pages 102-117.
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    3. Jonas Ingels & Broos Maenhout, 2017. "Employee substitutability as a tool to improve the robustness in personnel scheduling," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 39(3), pages 623-658, July.
    4. Jose L. Andrade-Pineda & David Canca & Pedro L. Gonzalez-R & M. Calle, 2020. "Scheduling a dual-resource flexible job shop with makespan and due date-related criteria," Annals of Operations Research, Springer, vol. 291(1), pages 5-35, August.

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