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Maximizing Dual Function by Genetic Algorithm – A New Approach for Optimal Manpower Planning

  • Xiaoqiang Cai
  • Yongjian Li
  • Fengsheng Tu
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4114)

Abstract

We propose a new approach to tackle the manpower planning problem with multiple types of jobs in a long planning horizon, where dynamic demands for manpower must be fulfilled by allocating enough number of employees with qualified skills. We first apply Lagrangean relaxation to decompose the problem into a number of subproblems, each corresponding to one skill type, and then develop a coordination scheme based on a Genetic algorithm, which updates the Lagrangean multipliers to maximize the dual objective function. We report computational results, which demonstrate the effectiveness of our approach.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Xiaoqiang Cai
    • 1
    • 3
  • Yongjian Li
    • 2
  • Fengsheng Tu
    • 3
  1. 1.Department of System Engineering & Engineering Management, The Chinese University of HongKong, Shatin N. T., Hong KongChina
  2. 2.Business School, Nankai University, Tianjin 300071China
  3. 3.College of Information Technical Science, Nankai University, Tianjin 300071China

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