New Local Search Procedure for Workforce Planning Problem
Online veröffentlicht: 31. Dez. 2020
Seitenbereich: 40 - 48
Eingereicht: 20. Aug. 2020
Akzeptiert: 23. Okt. 2020
DOI: https://doi.org/10.2478/cait-2020-0059
Schlüsselwörter
© 2020 Stefka Fidanova et al., published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Optimization of workforce planning is important for any production area. This leads to an improvement in production process. The aim is minimization of the assignment costs of the workers, who will do the jobs. The problem is to select and assign employers to the jobs to be performed. The constraints are very strong, coming both from the specifics of the production process and from the legislation. Sometimes it is difficult to find feasible solutions. The complexity of the problem is very high and the needed number of calculations is exponential, therefore only specially developed algorithms can be applied. The objective is to minimize the assignment cost, while respecting all requirements. We propose a new hybrid metaheuristic algorithm to solve the workforce-planning problem, which is a combination between Ant Colony Optimization (ACO) and suitable local search procedure.