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New approach for performance score analysis of m-polar Fuzzy ELECTRE-I method

Author

Listed:
  • Madan Jagtap

    (Symbiosis Institute of Operations Management, Nashik Campus, Constituent of Symbiosis International (Deemed University))

  • Prasad Karande

    (Veermata Jijabai Technological Institute)

Abstract

Performance score analysis is an important step in the MCDM technique's rank evaluation. If outranking relationships are plotted on a digraph, the m-polar fuzzy ELECTRE-I approach can be used to approximate rank evaluation but not to properly rank evaluate. We can determine the ranks of alternatives using the m-polar fuzzy ELECTRE-I and an approximate graphical solution for the rank evaluation. Instead of using a graphic solution for outranking relationships, this paper introduces a new approach for evaluating rank based on performance scores. The event of occurrence of the concordance and discordance indices is used to evaluate the performance score of specific alternatives outranking relationships. The rank of alternatives is determined by sorting performance scores in descending order. The performance score analysis of the m-polar fuzzy ELECTRE-I method's findings are validated utilizing four separate case studies that focus on the selection of cutting fluid, flexible manufacturing systems (FMS), robotics, and non-traditional machining techniques. The case studies' Spearman's rank correlation coefficient values are 0.9285, 0.9285, 0.78570, and 0.6190, respectively. The ELECTRE-I methodology follows a similar procedure.

Suggested Citation

  • Madan Jagtap & Prasad Karande, 2024. "New approach for performance score analysis of m-polar Fuzzy ELECTRE-I method," OPSEARCH, Springer;Operational Research Society of India, vol. 61(4), pages 2095-2130, December.
  • Handle: RePEc:spr:opsear:v:61:y:2024:i:4:d:10.1007_s12597-024-00775-z
    DOI: 10.1007/s12597-024-00775-z
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    References listed on IDEAS

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    1. Prasad Karande & Shankar Chakraborty, 2013. "Evaluation and selection of flexible manufacturing systems using MACBETH method," International Journal of Services and Operations Management, Inderscience Enterprises Ltd, vol. 16(1), pages 123-144.
    2. R. Venkata Rao & Dinesh Singh, 2011. "Evaluating flexible manufacturing systems using Euclidean distance-based integrated approach," International Journal of Decision Sciences, Risk and Management, Inderscience Enterprises Ltd, vol. 3(1/2), pages 32-53.
    3. Kulak, Osman & Kahraman, Cengiz, 2005. "Multi-attribute comparison of advanced manufacturing systems using fuzzy vs. crisp axiomatic design approach," International Journal of Production Economics, Elsevier, vol. 95(3), pages 415-424, March.
    4. R. Venkata Rao, 2009. "Flexible Manufacturing System selection using an improved compromise ranking method," International Journal of Industrial and Systems Engineering, Inderscience Enterprises Ltd, vol. 4(2), pages 198-215.
    5. Vijay Manikrao Athawale & Prasenjit Chatterjee & Shankar Chakraborty, 2012. "Selection of industrial robots using compromise ranking method," International Journal of Industrial and Systems Engineering, Inderscience Enterprises Ltd, vol. 11(1/2), pages 3-15.
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