ACO for Workforce Planning
Author:
Publisher
Springer International Publishing
Link
http://link.springer.com/content/pdf/10.1007/978-3-030-67380-2_9
Reference23 articles.
1. Fidanova, S., Luquq, G., Roeva, O., Paprzycki, M., Gepner, P.: Ant colony optimization algorithm for workforce planning. FedCSIS’2017, pp. 415–419. IEEE Xplorer (2017)
2. Fidanova, S., Luquq, G., Roeva, O., Paprzycki, M., Gepner, P.: Hybrid Ant colony optimization algorithm for workforce planning. Ann. Comput. Sci. Inf. Syst. 15, 233–236 (2018). ISSN:2300-5963, https://doi.org/10.15439/2018F47
3. Hewitt, M., Chacosky, A., Grasman, S., Thomas, B.: Integer programming techniques for solving non-linear workforce planning models with learning. Eur. J. Oper. Res. 242(3), 942–950 (2015)
4. Othman, M., Bhuiyan, N., Gouw, G.: Integrating workers’ differences into workforce planning. Comput. Ind. Eng. 63(4), 1096–1106 (2012)
5. Campbell, G.: A two-stage stochastic program for scheduling and allocating cross-trained workers. J. Oper. Res. Soc. 62(6), 1038–1047 (2011)
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