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<p>This paper discusses the significance of the multi-level multiobjective quadratic fractional programming problem (ML-MOQFPP) within hierarchical organizations and the challenges it faces in achieving success. It introduces the M-TOPSIS approach, which aims to address these challenges by utilizing membership functions and distances of the positive and negative ideal solutions at each level. The primary objective of M-TOPSIS is to maximize membership goals while minimizing deviational variables, thereby obtaining optimal outcomes for decision variables. It elaborates on the problem formulation involving multi-level multiobjective decision-making with quadratic constraints, emphasizing the minimization of fractional quadratic functions at each level through the M-TOPSIS algorithm. Additionally, it provides an illustrative numerical example and algorithm to validate the proposed methodology, concluding with comparative discussions against existing approaches.</p>

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Optimizing multi-level decision-making: M-TOPSIS approach for quadratic fractional multiobjective problems

  • 期刊论文

  • 发表日期：

    2025年7月4日

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  • Rozy Rani,
  • Vandana Goyal,
  • Deepak Gupta

摘要

This paper discusses the significance of the multi-level multiobjective quadratic fractional programming problem (ML-MOQFPP) within hierarchical organizations and the challenges it faces in achieving success. It introduces the M-TOPSIS approach, which aims to address these challenges by utilizing membership functions and distances of the positive and negative ideal solutions at each level. The primary objective of M-TOPSIS is to maximize membership goals while minimizing deviational variables, thereby obtaining optimal outcomes for decision variables. It elaborates on the problem formulation involving multi-level multiobjective decision-making with quadratic constraints, emphasizing the minimization of fractional quadratic functions at each level through the M-TOPSIS algorithm. Additionally, it provides an illustrative numerical example and algorithm to validate the proposed methodology, concluding with comparative discussions against existing approaches.