Pharmaceutical 3PL supplier selection using interval-valued intuitionistic fuzzy TOPSIS

C. Kahraman, S. Çebi, Sezi Cevik Onar, Başar Öztayşi
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引用次数: 2

Abstract

Third party logistics (3PL) supplier selection problem is a multi-criteria selection problem that is frequently discussed in the literature. Medicine is a fundamental element for human health and drug transportation must be carried out on time and under conditions that will ensure that the drug does not lose its physical properties. Therefore, the pharmaceutical industry is one of the foremost and most important sectors in 3PL. In this multi-criteria problem where the evaluation criteria are linguistic rather than numerical, vagueness and impreciseness in evaluations can only be handled with the help of fuzzy sets. With the help of intuitionistic fuzzy sets, one of the new extensions of fuzzy sets, the vagueness and impreciseness here will be discussed and the 3PL supplier selection problem will be tried to be solved with the TOPSIS method, which is one of the most used MCDM methods in the literature. The use of Interval-Valued Intuitionistic Fuzzy sets will add more flexibility and accuracy to the assessment. Thus, the Interval-Valued Intuitionistic Fuzzy TOPSIS method is used to solve the 3PL supplier selection problem and the robustness of the decisions taken is tested with a sensitivity analysis.
基于区间值直觉模糊TOPSIS的医药第三方物流供应商选择
第三方物流(3PL)供应商选择问题是一个多标准选择问题,经常在文献中讨论。医药是人类健康的基本要素,药品运输必须按时进行,并在保证药品不失去其物理性质的条件下进行。因此,制药行业是最重要和最重要的部门之一,在第三方物流。在这种评价标准为语言而非数值的多准则问题中,评价中的模糊性和不精确性只能借助模糊集来处理。本文将借助模糊集的一种新扩展——直觉模糊集,讨论其中的模糊性和不精确性,并尝试使用文献中最常用的MCDM方法之一TOPSIS方法来解决第三方物流供应商选择问题。区间值直觉模糊集的使用将为评估增加更多的灵活性和准确性。因此,采用区间值直觉模糊TOPSIS方法解决第三方物流供应商选择问题,并通过灵敏度分析检验决策的鲁棒性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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