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<p>As a consequence of notable demand for diverse electronic devices, electronic waste (e-waste) is the fastest increasing form of waste that can have adversative impacts on the human being, animals and environment by polluting the natural resources. It is made up of longstanding or end-of-life electronic appliances that are naturally rejected by their original possessors because of their short lifespan. Improper handling of e-waste disposal can cause long-term and undesirable risks to public health, the environment and those managing it. As e-waste contains a number of hazardous as well as valuable materials, therefore, selecting an appropriate e-waste management strategy is important before its treatment. This work aims to develop hybrid ranking framework for assessing and prioritizing the strategies of e-waste management (EWM) with uncertain information. For this purpose, new score function and distance measure are introduced on “<i>intuitionistic fuzzy sets</i> (IFSs)”. The developed ranking approach is categorized in the following stages. First stage computes the weight of invited decision-experts (DEs) using IF-score function-based method and further creates an aggregated decision-matrix by uniting diverse opinions of DEs concerning the performance of each option over given attributes. Second stage evaluates the weights of criteria with an integrated weight-determining structure that combines objective weight by “<i>MEthod based on the Removal Effects of Criteria</i> (MEREC)” and the subjective weight via “<i>Relative closeness coefficient</i> (RCC)” with intuitionistic fuzzy information (IFI). Based on these stages, the third stage of this framework presents an incorporated “<i>IF-additive ratio assessment</i> (IF-ARAS)” approach to rank the alternatives. This paper further applies proposed hybrid framework on a case study of EWM strategies, which illustrates its practicality and feasibility. Lastly, sensitivity and comparative study are presented to test the stability and robustness of proposed hybrid framework on IFSs setting.</p>

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An intuitionistic fuzzy score function and distance measure-based decision-making model for prioritizing sustainable strategies for electronic waste management

  • 期刊论文

  • 发表日期：

    2026年3月27日

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  • Arunodaya Raj Mishra,
  • Pratibha Rani,
  • Shashi Shekhar,
  • Ahmad M. Alshamrani,
  • Adel Fahad Alrasheedi

摘要

As a consequence of notable demand for diverse electronic devices, electronic waste (e-waste) is the fastest increasing form of waste that can have adversative impacts on the human being, animals and environment by polluting the natural resources. It is made up of longstanding or end-of-life electronic appliances that are naturally rejected by their original possessors because of their short lifespan. Improper handling of e-waste disposal can cause long-term and undesirable risks to public health, the environment and those managing it. As e-waste contains a number of hazardous as well as valuable materials, therefore, selecting an appropriate e-waste management strategy is important before its treatment. This work aims to develop hybrid ranking framework for assessing and prioritizing the strategies of e-waste management (EWM) with uncertain information. For this purpose, new score function and distance measure are introduced on “intuitionistic fuzzy sets (IFSs)”. The developed ranking approach is categorized in the following stages. First stage computes the weight of invited decision-experts (DEs) using IF-score function-based method and further creates an aggregated decision-matrix by uniting diverse opinions of DEs concerning the performance of each option over given attributes. Second stage evaluates the weights of criteria with an integrated weight-determining structure that combines objective weight by “MEthod based on the Removal Effects of Criteria (MEREC)” and the subjective weight via “Relative closeness coefficient (RCC)” with intuitionistic fuzzy information (IFI). Based on these stages, the third stage of this framework presents an incorporated “IF-additive ratio assessment (IF-ARAS)” approach to rank the alternatives. This paper further applies proposed hybrid framework on a case study of EWM strategies, which illustrates its practicality and feasibility. Lastly, sensitivity and comparative study are presented to test the stability and robustness of proposed hybrid framework on IFSs setting.