An adapted analytic hierarchy process for the supplier selection : model validation for a textile industry application

Abstract

Nowadays, it becomes increasingly important to efficiently manage business resources so that companies become more competitive in the market. Bearing in mind the current crisis (e.g., lack of components, economic constraints), it has become increasingly difficult to make a cautious selection of suppliers for the industrial context. The paradigm for suppliers’ selection and evaluation has been changing and may include different criteria, which is difficult to compare without a decision support system. Price is no longer the companies’ exclusive main concern given the difficulty in accessing raw materials or components. Environmental sustainability criteria have been introduced as a relevant factor to consider when choosing a new supplier. The delivery time, the quality of the materials, the flexibility, the capacity of response and the costs associated with he logistics have become criteria with greater weight in the final decision. Faced with this diversity of criteria, companies increasingly need to have systems that can help in their decision-making process. In this work, it is proposed an adapted analytic hierarchy process model for supplier selection, applied in a textile company. According to the diversity of criteria, a multi-criteria decision support model was implemented that considers both quantitative and qualitative criteria. The model is adapted from an analytic hierarchy process and assigns a weighting to each supplier, considering the different criteria. This algorithm was developed in Python. The final output is made available through a ranking system. At the end of the process, the decision maker can select the most promising supplier (supplier A with a weight of 29.3%) for the defined criteria, allowing a more informed decision by the company.