Workforce planning with parallel algorithms

  • Authors:
  • Enrique Alba;Gabriel Luque;Francisco Luna

  • Affiliations:
  • Department of Languages and Computational Sciences, University of Málaga, Málaga, Spain;Department of Languages and Computational Sciences, University of Málaga, Málaga, Spain;Department of Languages and Computational Sciences, University of Málaga, Málaga, Spain

  • Venue:
  • IPDPS'06 Proceedings of the 20th international conference on Parallel and distributed processing
  • Year:
  • 2006

Quantified Score

Hi-index 0.00

Visualization

Abstract

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 that requires modern techniques to be solved adequately. In this work, we describe the development of two parallel metaheuristic methods, a parallel genetic algorithm and a parallel scatter search, 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.