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Journal of Mathematical Modelling and Algorithms

, Volume 6, Issue 3, pp 509–528 | Cite as

Parallel Metaheuristics for Workforce Planning

  • Enrique Alba
  • Gabriel Luque
  • Francisco Luna
Article

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 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 words

workforce planning parallel metaheuristics parallel genetic algorithm parallel scatter search parallel hybrid genetic algorithm 

Mathematics Subject Classifications (2000)

68W15 90C27 90C59 

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Copyright information

© Springer Science + Business Media B.V. 2007

Authors and Affiliations

  1. 1.Department of Languages and Computational SciencesUniversity of MálagaMálagaSpain

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