Providing a Model for Assessing Pharmaceutical Industries Supply Chain Sustainability Using Adaptive Neuro- Fuzzy Inference System (ANFIS)

The health system has one of the most complex supply chains in the world to deal with human health and well-being. The pharmaceutical supply chain is part of this system. For this reason, the purpose of this study is to develop a model to evaluate supply chain sustainability in this industry.

First, by reviewing previous studies, indicators related to supply chain sustainability in economic, social, environmental and governance dimensions were extracted. Then, using a survey method to implement the model designed in ANFIS, a questionnaire was used to evaluate the sustainability factors in the case study.

The designed ANFISs with 50 training courses achieved acceptable error rates. In the economic and social dimension, the trend of sustainability changes was initially decreasing and then increasing. In the environmental dimension where negative indicators were considered, the trend is quite decreasing. In the governance dimension, the trend of incremental stability changes is. In the present study, the root mean square error (RMSE) is considered as a criterion for model validation.

To improve the condition, sustainability must first be evaluated and measured so that the results can be quantified after the improvement measures. Based on the findings, it can be concluded that the model designed in ANFIS is a good tool for assessing sustainability.