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Hamming distance method with subjective and objective weights for personnel selection.

R Saad1, M Z Ahmad1, M S Abu1

  • 1Institute of Engineering Mathematics, Universiti Malaysia Perlis, Pauh Putra Main Campus, 02600 Arau, Perlis, Malaysia.

Thescientificworldjournal
|May 1, 2014
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Summary

This study introduces a new fuzzy approach for personnel selection using the Hamming distance method with subjective and objective weights (HDMSOW). This method effectively handles incomplete information in complex decision-making scenarios.

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Area of Science:

  • Operations Research
  • Decision Science
  • Management Science

Background:

  • Multicriteria decision making (MCDM) is widely applied to personnel selection.
  • Accurate definition of alternatives, criteria, and weights is crucial for effective MCDM.
  • Fuzzy data, arising from incomplete or unobtainable information, presents challenges in MCDM.

Purpose of the Study:

  • To propose a novel approach for personnel selection problems.
  • To integrate fuzzy set theory with the Hamming distance method for handling vagueness.
  • To develop a robust method for determining subjective and objective weights in personnel selection.

Main Methods:

  • The proposed approach utilizes the Hamming distance method with subjective and objective weights (HDMSOW).
  • Fuzzy set theory is incorporated to manage situations with vague or uncertain data.
  • Fuzzy Shannon's entropy is employed to determine objective weights for attributes.
  • Subjective weights are aggregated into a comparable scale.

Main Results:

  • The study presents a new methodology, HDMSOW, for personnel selection.
  • The approach successfully incorporates fuzzy logic to address data uncertainty.
  • A numerical example demonstrates the practical application and effectiveness of the proposed method.

Conclusions:

  • The developed HDMSOW approach offers a viable solution for personnel selection under uncertainty.
  • Integrating fuzzy set theory enhances the robustness of MCDM in personnel selection.
  • The method provides a structured way to determine both objective and subjective weights for improved decision-making.