Parallel Metaheuristics for Workforce Planning
- 97 Downloads
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.
Key wordsworkforce planning parallel metaheuristics parallel genetic algorithm parallel scatter search parallel hybrid genetic algorithm
Mathematics Subject Classifications (2000)68W15 90C27 90C59
Unable to display preview. Download preview PDF.
- 1.Aardal, K.: Capacitated facility location: separation algorithm and computational experience. Math. Program. 81, 149–175 (1998)Google Scholar
- 3.Alba, E., Luque, G., Luna, F.: Workforce planning with parallel algorithms. IPDPS-NIDISC’06, 246 (2006)Google Scholar
- 5.Glover, F., Kochenberger, G., Laguna, M., Wubbena, T.: Selection and assignment of a skilled workforce to meet job requirements in a fixed planning period. In: MAEB’04, pp. 636–641 (2004)Google Scholar
- 6.Glover, F., Laguna, M., Martí, R.: Fundamentals of scatter search and path relinking. Control Cybern. 39(3), 653–684 (2000)Google Scholar
- 7.Holland, J.: Adaptation in Natural and Artificial Systems. (second edition) MIT, Cambridge, Massachusetts (1992)Google Scholar
- 10.Laguna, M., Wubbena, T.: Modeling and solving a selection and assignment problem. In: Golden, B., Raghavan, S., Wasil, E. (eds.) The Next Wave in Computing, Optimization, and Decision Technologies, pp. 149–162 (2005)Google Scholar