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Heuristics for workforce planning with worker differences

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  • Fowler, John W.
  • Wirojanagud, Pornsarun
  • Gel, Esma S.

Abstract

This study considers decisions in workforce management assuming individual workers are inherently different as measured by general cognitive ability (GCA). A mixed integer programming (MIP) model that determines different staffing decisions (i.e., hire, cross-train, and fire) in order to minimize workforce related costs over multiple periods is described. Solving the MIP for a large problem instance size is computationally burdensome. In this paper, two linear programming (LP) based heuristics and a solution space partition approach are presented to reduce the computational time. A genetic algorithm was also implemented as an alternative method to obtain better solutions and for comparison to the heuristics proposed. The heuristics were applied to realistic manufacturing systems with a large number of machine groups. Experimental results shows that performance of the LP based heuristics performance are surprisingly good and indicate that the heuristics can solve large problem instances effectively with reasonable computational effort.

Suggested Citation

  • Fowler, John W. & Wirojanagud, Pornsarun & Gel, Esma S., 2008. "Heuristics for workforce planning with worker differences," European Journal of Operational Research, Elsevier, vol. 190(3), pages 724-740, November.
    • Handle: RePEc:eee:ejores:v:190:y:2008:i:3:p:724-740
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    References listed on IDEAS

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    2. De Bruecker, Philippe & Van den Bergh, Jorne & Beliën, Jeroen & Demeulemeester, Erik, 2015. "Workforce planning incorporating skills: State of the art," European Journal of Operational Research, Elsevier, vol. 243(1), pages 1-16.
    3. De Bruecker, Philippe & Beliën, Jeroen & Van den Bergh, Jorne & Demeulemeester, Erik, 2018. "A three-stage mixed integer programming approach for optimizing the skill mix and training schedules for aircraft maintenance," European Journal of Operational Research, Elsevier, vol. 267(2), pages 439-452.
    4. Ulmer, Marlin & Nowak, Maciek & Mattfeld, Dirk & Kaminski, Bogumił, 2020. "Binary driver-customer familiarity in service routing," European Journal of Operational Research, Elsevier, vol. 286(2), pages 477-493.
    5. Komarudin, & Guerry, Marie-Anne & De Feyter, Tim & Vanden Berghe, Greet, 2013. "The roster quality staffing problem – A methodology for improving the roster quality by modifying the personnel structure," European Journal of Operational Research, Elsevier, vol. 230(3), pages 551-562.
    6. Corominas, Albert & Lusa, Amaia & Olivella, Jordi, 2012. "A detailed workforce planning model including non-linear dependence of capacity on the size of the staff and cash management," European Journal of Operational Research, Elsevier, vol. 216(2), pages 445-458.
    7. Lin, Shih-Wei & Ying, Kuo-Ching, 2014. "Minimizing shifts for personnel task scheduling problems: A three-phase algorithm," European Journal of Operational Research, Elsevier, vol. 237(1), pages 323-334.
    8. Farahani, Poorya & Grunow, Martin & Akkerman, Renzo, 2013. "Design and operations planning of municipal foodservice systems," International Journal of Production Economics, Elsevier, vol. 144(1), pages 383-396.
    9. Valeva, Silviya & Hewitt, Mike & Thomas, Barrett W. & Brown, Kenneth G., 2017. "Balancing flexibility and inventory in workforce planning with learning," International Journal of Production Economics, Elsevier, vol. 183(PA), pages 194-207.
    10. Battaïa, Olga & Delorme, Xavier & Dolgui, Alexandre & Hagemann, Johannes & Horlemann, Anika & Kovalev, Sergey & Malyutin, Sergey, 2015. "Workforce minimization for a mixed-model assembly line in the automotive industry," International Journal of Production Economics, Elsevier, vol. 170(PB), pages 489-500.
    11. Hewitt, Mike & Chacosky, Austin & Grasman, Scott E. & Thomas, Barrett W., 2015. "Integer programming techniques for solving non-linear workforce planning models with learning," European Journal of Operational Research, Elsevier, vol. 242(3), pages 942-950.
    12. Akl, Amany M. & El Sawah, Sondoss & Chakrabortty, Ripon K. & Turan, Hasan Hüseyin, 2022. "A Joint Optimization of Strategic Workforce Planning and Preventive Maintenance Scheduling: A Simulation–Optimization Approach," Reliability Engineering and System Safety, Elsevier, vol. 219(C).
    13. Gang Li & Joy M. Field & Hongxun Jiang & Tian He & Youming Pang, 2019. "Decision Models for Workforce and Technology Planning in Services," Papers 1909.12829, arXiv.org.

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