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.
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Anzaldua, R., Burt, C., Edmonds, H., Lehmann, K., Song, G. (2018). Multi-objective Large-Scale Staff Allocation. In: Kliewer, N., Ehmke, J., Borndörfer, R. (eds) Operations Research Proceedings 2017. Operations Research Proceedings. Springer, Cham. https://doi.org/10.1007/978-3-319-89920-6_76
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DOI: https://doi.org/10.1007/978-3-319-89920-6_76
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Online ISBN: 978-3-319-89920-6
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