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Multi-objective Large-Scale Staff Allocation

In: Operations Research Proceedings 2017

Author

Listed:
  • Roberto Anzaldua

    (Satalia)

  • Christina Burt

    (Satalia)

  • Harry Edmonds

    (Satalia)

  • Karsten Lehmann

    (Satalia)

  • Guangyan Song

    (Satalia)

Abstract

Satalia is working with a multinational company that needs to have a team of 10 people spend 4 months every year manually assigning 1,000 staff to perform 10,000 jobs on 2,000 projects. This is a massive undertaking, in part because of the scale of the problem and in part because the problem is multi-objective with 57 hard and soft business rules. The task can be formulated as a large-scale scheduling problem. We demonstrate that our optimisation methods can unlock substantial savings in company work-hours while also improving quality as measured across a range of objectives. In this paper, we will outline the heuristic and exact approaches utilised, describe some of the many challenges of such a real-world problem, and show how we overcame them.

Suggested Citation

  • Roberto Anzaldua & Christina Burt & Harry Edmonds & Karsten Lehmann & Guangyan Song, 2018. "Multi-objective Large-Scale Staff Allocation," Operations Research Proceedings, in: Natalia Kliewer & Jan Fabian Ehmke & Ralf Borndörfer (ed.), Operations Research Proceedings 2017, pages 573-579, Springer.
    • Handle: RePEc:spr:oprchp:978-3-319-89920-6_76
    DOI: 10.1007/978-3-319-89920-6_76
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