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Presentation of Multi-Skill Workforce Scheduling Model and Solving the Model Using Meta-Heuristic Algorithms

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Listed:
  • Iman Fozveh
  • Hooman Salehi
  • Kamran Mogharehabed

Abstract

In the present article, a multi-objective mathematical model for scheduling multi-skilled multi-objective workforce has been proposed with the aims of minimizing the number of night-shift engineers, minimizing the total cost of workforce and maximizing the number of engaged workforce. To solve the proposed model for scheduling workforce, bee colony optimization algorithm and DE algorithm have been employed, and in order to investigate the efficiency of these two algorithms, the results have been compared with each other in terms of quality, dispersion and uniformity factors. In order to solve the model three sample problems (40, 70 and 280 workforce) were designed and then solved by the two mentioned algorithms. Bee algorithm is able to find higher-quality answers. Also the results of the comparison of dispersion and uniformity index indicate that bee colony algorithm is able to find answers with more dispersion and more homogeneous than DE algorithm. The comparison of solution time of both algorithms indicate that bee colony algorithm is faster than DE algorithm and needs less time to reach quality, dispersed and homogenous answers.

Suggested Citation

  • Iman Fozveh & Hooman Salehi & Kamran Mogharehabed, 2016. "Presentation of Multi-Skill Workforce Scheduling Model and Solving the Model Using Meta-Heuristic Algorithms," Modern Applied Science, Canadian Center of Science and Education, vol. 10(2), pages 194-194, February.
    • Handle: RePEc:ibn:masjnl:v:10:y:2015:i:2:p:194
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    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

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