Evaluation and Selection of Predicaments in Pharmaceutical Supply Chain using AHP under Fuzzy Environment

Frontiers in Automobile and Mechanical Engineering

Nikhil, E.V.S.^1 ; Sai Ram, V.^1 ; Charan Yadav, V.^1 ; Kumar, Kalla Kiran^1 ; Nagaraju, Dega^2

B.Tech Mechanical Engineering, VIT University, Vellore, Tamil Nadu

632014, India^1

School of Mechanical Engineering, VIT University, Vellore, Tamil Nadu

632014, India^2

关键词: Evaluation and selections;    Fuzzy analytical hierarchy process;    Globalization of the business;    Multi-criteria decision making technique;    Pharmaceutical supply chains;    Regulatory requirements;    Selection and evaluations;    Technical information;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/197/1/012061/pdf
DOI  :  10.1088/1757-899X/197/1/012061

来源: IOP

【 摘 要 】

Pharmaceutical sector plays an important role in the medical and health system. Due to the globalization of the business, increasing demand and supply for drugs, growing regulatory requirements, all stages of the pharmaceutical supply chain (SC) are facing numerous predicaments. The traditional way of selection and evaluation of these predicaments is customarily done using technical information. This approach lacks the ability to project the burning issue that to be addressed first. Hence, a computing method of selecting the crucial issue from the existing issues is essential in a pharmaceutical supply chain. This paper considers seven different predicaments as criteria and five sub-criteria under each main predicament of a pharmaceutical supply chain. The intention of this project is to manifest the process of assessing and selecting the issue that to be addressed first by using multi-criteria decision making technique (MCDM), i.e., fuzzy analytical hierarchy process (FAHP). The criteria and sub-criteria weights are calculated and priority assessment of the predicaments is done by using FAHP. Finally, from the findings of this work, the predicaments are ranked from most important to least important. This gives information to the decision maker (DM) to solve the issue that is affecting the SC the most with respect to the others.