| Article ID: | iaor20082971 |
| Country: | Netherlands |
| Volume: | 6 |
| Issue: | 3 |
| Start Page Number: | 509 |
| End Page Number: | 528 |
| Publication Date: | Sep 2007 |
| Journal: | Journal of Mathematical Modelling and Algorithms |
| Authors: | Alba Enrique, Luque Gabriel, Luna Francisco |
| Keywords: | heuristics: genetic algorithms |
Workforce planning is an important activity that enables organizations to determine the workforce needed for continued success. A workforce planning problem is a very complex task requiring modern techniques to be solved adequately. In this work, we describe the development of three parallel metaheuristic methods, a parallel genetic algorithm, a parallel scatter search, and a parallel hybrid genetic algorithm, which can find high-quality solutions to 20 different problem instances. Our experiments show that parallel versions do not only allow to reduce the execution time but they also improve the solution quality.