دانلود رایگان مقاله انگلیسی بررسی ساختاری مدل های کمی زنجیره تامین دارویی - هینداوی 2017

The aim of this review is to identify and provide a structured overview of quantitative models in the pharmaceutical supply chain, a subject not exhaustively studied in the previous reviews on healthcare logistics related mostly to quantitative models in healthcare or logistics studies in hospitals. The models are classified into three categories of classification: network design, inventory models, and optimization of a pharmaceutical supply chain. A taxonomy for each category is shown describing the principal features of each echelon included in the review; this taxonomy allows the readers to identify easily a paper based on the actors of the pharmaceutical supply chain. The search process included research articles published in the databases between 1984 and November 2016. In total 46 studies were included. In the review process we found that in the three fields the most common source of uncertainty used is the demand in the 56% of the cases. Within the review process we can conclude that most of the articles in the literature are focused on the optimization of the pharmaceutical supply chain and inventory models but the field on supply chain network design is not deeply studied.

5. Conclusions

In this paper we present a literature review of quantitative models of the pharmaceutical supply chain. We identify three classification categories in terms of strategic, tactical, and operational decisions. The source of uncertainty used in the models is presented in this review, with the finding that the majority of articles use a stochastic form of uncertainty in some of the echelons of the chain. We found in the taxonomy proposed that 52% of the articles correspond to network design, 28% correspond to inventory problems, and 20% correspond to supply chain optimization models.

Several deterministic models are presented, but in the majority of cases the use of techniques is developed under uncertainty. Most of the articles involve stochastic approximations, and only a few uses an alternative approximation of uncertainty, for example, fuzzy logic and robust optimization, among others. In network design 56% of the articles use the demand as deterministic and 22% as stochastic and 22% of the articles used both types of demand while in inventory models 92% of the articles use the demand as stochastic and 8% as deterministic. In supply chain optimization 52% of the articles use the demand as deterministic and 48% as stochastic.