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TODIM Approach for Selection of Inventory Policy in Supply Chain
Author(s) -
Prabjot Kaur,
Bijay Lal Pradhan,
A V N S B K Soumya Priya
Publication year - 2022
Publication title -
mathematical problems in engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.262
H-Index - 62
eISSN - 1026-7077
pISSN - 1024-123X
DOI - 10.1155/2022/5959116
Subject(s) - vagueness , supply chain , operations research , fuzzy logic , quality (philosophy) , computer science , selection (genetic algorithm) , rank (graph theory) , sensitivity (control systems) , supply chain management , ranking (information retrieval) , risk analysis (engineering) , business , marketing , mathematics , engineering , artificial intelligence , philosophy , epistemology , combinatorics , electronic engineering
TODIM-based multicriteria decision-making approach for assessing inventory policy in a Pythagorean fuzzy environment is proposed in this study. In supply chain, inventory appears in several forms. For effective supply chain, management businesses must choose an effective inventory policy. It is difficult to rank inventory policies. Inventory policy selection and evaluation include a procedure that can be thought about, checked after some time, and ideally improved through certain measures. Determination of the right inventory control policy is a challenge in the dynamic business environment as it enables organizations to gain an upper hand in terms of cost, quality, and service, which in turn provides a vital step in fulfilling the requirements of the customer. The multicriteria question has qualitative and quantitative factors that are vague and contradictory. Such variables are not necessarily clear and often suffer vagueness owing to the inconsistent existence of the gathered data. In the Pythagorean fuzzy setting, they are therefore considered to eliminate this vagueness by assigning membership and nonmembership roles to these factors. Finally, in this article, we performed a sensitivity analysis to demonstrate the stability of our model and to illustrate the utility of implementing such algorithms.

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