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Fuzzy Method Based on the Removal Effects of Criteria (MEREC) for Determining Objective Weights in Multi-Criteria Decision-Making Problems

Author

Listed:
  • Mohamad Shahiir Saidin

    (Department of Mathematics and Statistics, Faculty of Science, Universiti Putra Malaysia, Serdang 43400, Selangor, Malaysia)

  • Lai Soon Lee

    (Department of Mathematics and Statistics, Faculty of Science, Universiti Putra Malaysia, Serdang 43400, Selangor, Malaysia
    Laboratory of Computational Statistics and Operations Research, Institute for Mathematical Research, Universiti Putra Malaysia, Serdang 43400, Selangor, Malaysia)

  • Siti Mahani Marjugi

    (Department of Mathematics and Statistics, Faculty of Science, Universiti Putra Malaysia, Serdang 43400, Selangor, Malaysia)

  • Muhammad Zaini Ahmad

    (Institute of Engineering Mathematics, Universiti Malaysia Perlis, Pauh Putra Main Campus, Arau 02600, Perlis, Malaysia)

  • Hsin-Vonn Seow

    (Nottingham University Business School, Faculty of Arts and Social Sciences, University of Nottingham Malaysia, Semenyih 43500, Selangor, Malaysia)

Abstract

In multi-criteria decision-making (MCDM) research, the criteria weights are crucial components that significantly impact the results. Many researchers have proposed numerous methods to establish the weights of the criterion. This paper provides a modified technique, the fuzzy method based on the removal effects of criteria (MEREC) by modifying the normalization technique and enhancing the logarithm function used to assess the entire performance of alternatives in the weighting process. Since MCDM problems intrinsically are ambiguous or complex, fuzzy theory is used to interpret the linguistic phrases into triangular fuzzy numbers. The comparative analyses were conducted through the case study of staff performance appraisal at a Malaysian academic institution and the simulation-based study is used to validate the effectiveness and stability of the presented method. The results of the fuzzy MEREC are compared with those from a few different objective weighting techniques based on the correlation coefficients, outlier tests and central processing unit (CPU) time. The results of the comparative analyses demonstrate that fuzzy MEREC weights are verified as the correlation coefficient values are consistent throughout the study. Furthermore, the simulation-based study demonstrates that even in the presence of outliers in the collection of alternatives, fuzzy MEREC is able to offer consistent weights for the criterion. The fuzzy MEREC also requires less CPU time compared to the existing MEREC techniques. Hence, the modified method is a suitable alternative and efficient for computing the objective criteria weights in the MCDM problems.

Suggested Citation

  • Mohamad Shahiir Saidin & Lai Soon Lee & Siti Mahani Marjugi & Muhammad Zaini Ahmad & Hsin-Vonn Seow, 2023. "Fuzzy Method Based on the Removal Effects of Criteria (MEREC) for Determining Objective Weights in Multi-Criteria Decision-Making Problems," Mathematics, MDPI, vol. 11(6), pages 1-20, March.
    • Handle: RePEc:gam:jmathe:v:11:y:2023:i:6:p:1544-:d:1104157
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    References listed on IDEAS

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    Cited by:

    1. Mohamad Shahiir Saidin & Lai Soon Lee & Hsin-Vonn Seow & Stefan Pickl, 2024. "Fuzzy Divergence Measure Based on Technique for Order of Preference by Similarity to Ideal Solution Method for Staff Performance Appraisal," Mathematics, MDPI, vol. 12(5), pages 1-28, February.
    2. Anas A. Makki & Reda M. S. Abdulaal, 2023. "A Hybrid MCDM Approach Based on Fuzzy MEREC-G and Fuzzy RATMI," Mathematics, MDPI, vol. 11(17), pages 1-19, September.
    3. Peng Liu & Tieyan Zhang & Furui Tian & Yun Teng & Miaodong Yang, 2024. "Optimized Grid Partitioning and Scheduling in Multi-Energy Systems Using a Hybrid Decision-Making Approach," Energies, MDPI, vol. 17(13), pages 1-21, July.

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