<abstract xmlns="http://www.w3.org/1999/xhtml"><p>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.</p></abstract>

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.

New Local Search Procedure for Workforce Planning Problem

Cybernetics and Information Technologies

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

{"article-title":"New Local Search Procedure for Workforce Planning Problem"}

Optimization of workforce planning is important for any production area. This leads to an improvement in production process. The aim is minimization of the...

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
Metaheuristics, ant colony optimization, local search, workforce planning, combinatorial optimization

© 2020 Stefka Fidanova et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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

SchlüsselwörterMetaheuristics, ant colony optimization, local search, workforce planning, combinatorial optimization

© 2020 Stefka Fidanova et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Schlüsselwörter
Metaheuristics, ant colony optimization, local search, workforce planning, combinatorial optimization