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A study of an EOQ model where the demand depends on time and varying number of tourists using fuzzy triangular norms

The fundamental prerequisite of decision making is how to aggregate individual expert’s preference information. For constructing various aggregation operators on intuitionistic fuzzy set, various kinds of t-norms and co-norms are the most significant tools. This work takes a closer look on various f...

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Detalles Bibliográficos
Autores principales: Karmakar, Snigdha, De, Sujit Kumar
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8985570/
https://www.ncbi.nlm.nih.gov/pubmed/35401854
http://dx.doi.org/10.1007/s12652-022-03821-0
Descripción
Sumario:The fundamental prerequisite of decision making is how to aggregate individual expert’s preference information. For constructing various aggregation operators on intuitionistic fuzzy set, various kinds of t-norms and co-norms are the most significant tools. This work takes a closer look on various fuzzy triangular norms and uses them for the first time in an economic order quantity (EOQ) model. Traditional economic theory has a paradigm shift on objective factors affecting demand such as price and income. Recently, behavioural economics gives more weightage to psychological and social factors that affect our preferences and choices in markets differently. As per literature survey concern, this paper may indeed be the first to adopt the concept of the number of variations of a tourist’s dependent demand in inventory management problems. Utilizing several triangular norms, we have characterized Attanassov (standard) and non-Attanassov’s (non-standard) feasible region. A case study has been performed for numerical illustration and model validation. A solution algorithm, has also been developed which proves Attanassov’s solution space is quite inferior to non-Attanassov’s domain. Finally, sensitivity analysis and graphical illustrations are also provided to justify the model. GRAPHICAL ABSTRACT: [Image: see text]