Mahuya Deb, Prabjot Kaur, Kandarpa Kumar Sarma



Inventory Policy Selection Using Intuitionistic Fuzzy LINMAP model

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Inventory constitutes the part and parcel of every business domain and therefore its control is one of the key areas for driving optimization initiatives in an organization. Different inventory control policies have received attention in recent times as they affect the overall cost, quality and service of organizations which faces threat from the dynamic business environment. Inventory policies are characterized on the basis of various attributes which may not be precise and lack proper information. Multiattribute decision making problems are often confronted with the innate problem of selection, evaluation or ranking of alternatives that are typically characterized by multiple and conflicting attributes. This paper is an attempt to develop a new methodology for solving multi-attribute inventory control policies using the concept of intuitionistic fuzzy sets (IFS).The theory of IFS provides a structure to deal with information of the real world which lack clarity and are imperfect and/or imprecise. This very concept can be seen as an alternative option to describe a fuzzy set in situations when the existing information is not enough to define a usual fuzzy set. The technique involves in developing a fuzzy linear programming for multidimensional analysis of preference (LINMAP) under intuitionistic fuzzy (IF) environment that reflects the relative preference of the factors that the decision maker adheres to. The DM’s preferences are arranged through pair-wise comparisons of alternatives and the one that has the shortest distance to the positive ideal solution (PIS) is considered the best solution


inventory policies, multi attribute decision making, LINMAP


Cite this paper

Mahuya Deb, Prabjot Kaur, Kandarpa Kumar Sarma. (2019) Inventory Policy Selection Using Intuitionistic Fuzzy LINMAP model. International Journal of Mathematical and Computational Methods, 4, 49-57


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