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Interval-valued dual hesitant fuzzy prioritized aggregation operators based on Archimedean t-conorm and t-norm and their applications to multi-criteria decision making

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Sarkar A. , Biswas A.

Archives of Control Sciences

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2021

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tom Vol. 31, No. 1

213--247

EN

Multi-criteria decision making (MCDM) technique and approach have been a trending topic in decision making and systems engineering to choosing the probable optimal options. The primary purpose of this article is to develop prioritized operators to multi-criteria decision making (MCDM) based on Archimedean t-conorm and t-norms (At-CN&t-Ns) under interval-valued dual hesitant fuzzy (IVDHF) environment. A new score function is defined for finding the rank of alternatives in MCDM problems with IVDHF information based on priority levels of criteria imposed by the decision maker. This paper introduces two aggregation operators: At-CN&t-N-based IVDHF prioritized weighted averaging (AIVDHFPWA), and weighted geometric (AIVDHFPWG) aggregation operators. Some of their desirable properties are also investigated in details. A methodology for prioritization-based MCDM is derived under IVDHF information. An illustrative example concerning MCDM problem about a Chinese university for appointing outstanding oversea teachers to strengthen academic education is considered. The method is also applicable for solving other real-life MCDM problems having IVDHF information.

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Linguistic 𝑞-rung orthopair fuzzy prioritized aggregation operators based on Hamacher 𝑡-norm and 𝑡-conorm and their applications to multicriteria group decision making

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Deb N. , Sarkar A. , Biswas A.

Archives of Control Sciences

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2022

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tom Vol. 32, No. 2

451--484

EN

The linguistic q-rung orthopair fuzzy (Lq-ROF) set is an important implement in the research area in modelling vague decision information by incorporating the advantages of q-rung orthopair fuzzy sets and linguistic variables. This paper aims to investigate the multicriteria decision group decision making (MCGDM) with Lq-ROF information. To do this, utilizing Hamacher t-norm and t-conorm, some Lq-ROF prioritized aggregation operators viz., Lq-ROF Hamacher prioritized weighted averaging, and Lq-ROF Hamacher prioritized weighted geometric operators are developed in this paper. The defined operators can effectively deal with different priority levels of attributes involved in the decision making processes. In addition, Hamacher parameters incorporated with the proposed operators make the information fusion process more flexible. Some prominent characteristics of the developed operators are also well-proven. Then based on the proposed aggregation operators, an MCGDM model with Lq-ROF context is framed. A numerical example is illustrated in accordance with the developed model to verify its rationality and applicability. The impacts of Hamacher and rung parameters on the achieved decision results are also analyzed in detail. Afterwards, a comparative study with other representative methods is presented in order to reflect the validity and superiority of the proposed approach.

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Influence of socio-demographic factors on the breastfeeding period of women in Bangladesh: a polytomous logistic regression model

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Islam M. , Afroja S. , Biswas A. , Khan M. S. , Khandker S.

Family Medicine & Primary Care Review

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2019

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nr 3

223-229

XX

Background. In Bangladesh, terrible degradation in the breastfeeding period has occurred with rapid urbanization in recent years that is causing a shortage of child nourishment. Identifying the risk factors of breastfeeding duration is important for planning nutritional programs and strategies. Objectives. This study tries to identify influential demographic and socio-economic factors that affect the breastfeeding period for reducing child nutrition deficiency. Material and methods. The study attempts to proceed with data collected from an observational study entitled the Bangladesh Demographic and Health Survey (BDHS) 2014. The breastfeeding period (Ordinal exogenous variable) is classified into three groups: 0–5-months, 6–23 months and at least 24 months. Gamma, chi-square and linear-by-linear statistics are used to identify the associated factors that have an impact on the breastfeeding period. A test of parallelism is conducted to evaluate the proportional odds. The polytomous logistic regression (PLR) model and the proportional odds (PO) model are used to find the marginal effect of demographic and socio-economic predictors that affect the breastfeeding period. Results. Parental educational attainment, wealth index, division, religion, mother’s BMI, drinking water source, household members, amenorrhea and abstaining, respectively, are the most significant factors that influence the breastfeeding period. The PLR model is also more precise than the PO model for indicating the marginal effect among those vital factors for the breastfeeding period. Conclusions. PLR is an appropriate model to recognize the effect of predictors of breastfeeding duration instead of the PO model and other measures.