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<p>Psychological Health is a very important factor in anyone’s life. It may affect both mental and physical health conditions. In this paper, we are interested in finding the weight of the psychological health-related criterion’s and ranking the related alternatives by using the well-known statistical techniques, the Analytic Hierarchy Process (AHP) and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) methods. For the aforementioned problem, we utilise the dataset of Indian women following the COVID-19 pandemic. This study collects data in linguistic terms from decision makers (DMs) who are already experts in the healthcare field. All the data are converted into Generalized Intuitionistic Pentagonal Fuzzy Numbers (GIPFN) to capture the uncertainty of the dataset. Furthermore, a new de-fuzzification method is proposed to de-fuzzify the fuzzy sets. From the given data, analysis the importance of each criterion and assign a weight to it using the AHP methodology. After that, apply the TOPSIS technique to prioritise the health facilities among the different age groups. The numerical illustrations are presented based on different age groups. Lastly, sensitivity analysis and comparative analysis are conducted to demonstrate the applicability of the methodology in psychological health-related applications.</p>

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Measuring most affected age group of women with respect to different psychological issues by uncertain MCDM methodology

  • 期刊论文

  • 发表日期：

    2026年2月7日

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  • Kamal Hossain Gazi,
  • Alaa Fouad Momena,
  • Aditi Biswas,
  • Anna Sobczak,
  • Soheil Salahshour,
  • Arijit Ghosh,
  • Sankar Prasad Mondal

摘要

Psychological Health is a very important factor in anyone’s life. It may affect both mental and physical health conditions. In this paper, we are interested in finding the weight of the psychological health-related criterion’s and ranking the related alternatives by using the well-known statistical techniques, the Analytic Hierarchy Process (AHP) and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) methods. For the aforementioned problem, we utilise the dataset of Indian women following the COVID-19 pandemic. This study collects data in linguistic terms from decision makers (DMs) who are already experts in the healthcare field. All the data are converted into Generalized Intuitionistic Pentagonal Fuzzy Numbers (GIPFN) to capture the uncertainty of the dataset. Furthermore, a new de-fuzzification method is proposed to de-fuzzify the fuzzy sets. From the given data, analysis the importance of each criterion and assign a weight to it using the AHP methodology. After that, apply the TOPSIS technique to prioritise the health facilities among the different age groups. The numerical illustrations are presented based on different age groups. Lastly, sensitivity analysis and comparative analysis are conducted to demonstrate the applicability of the methodology in psychological health-related applications.