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Proceedings of the 18th Conference on Computer Science and Intelligence Systems

Annals of Computer Science and Information Systems, Volume 35

Ant Colony Optimization for Workforce Planning with Hybridization

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DOI: http://dx.doi.org/10.15439/2023F9586

Citation: Proceedings of the 18th Conference on Computer Science and Intelligence Systems, M. Ganzha, L. Maciaszek, M. Paprzycki, D. Ślęzak (eds). ACSIS, Vol. 35, pages 955959 ()

Full text

Abstract. Production organization plays a key role in the success of any enterprise. Workforce planning and assignment is an important element of the production organization. Optimizing workforce planning can improve the overall organization of production. The main goal is to minimize the assignment cost of the workers who will perform the planned work. The problem is known to be NP-hard, therefore we will apply methods from the field of artificial intelligence. The problem is to select workers to be assigned to perform the jobs. This is a difficult optimization problem with very strict constraints. For this reason, most of the existing methods hardly find feasible solutions. We propose Ant Colony Optimization Algorithm with hybridization, combination with local search procedures. We compare and analyze their performance

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