Considering supply risk for supplier selection using an integrated framework of data envelopment analysis and neural networks

Abstract

For many years, supplier selection as an important multi-criteria decision has attracted both the researchers and practitioners. During recent years, high incidence of natural disasters, terrorism attacks, labor strikes and other kinds of risks, also known as disruptions, indicates the vulnerability of procurement process to these unpredicted events. In this study, a new framework is introduced to select suppliers while considering the supply risks. In the proposed framework, an expert determines the reliabilities of procurement elements (i.e., production, transportation and communication) based on some proposed risk factors. Then, a trained Multi-Layer Perceptron (MLP) network plays the role of the expert opinion for estimating the reliability scores. In addition to reliabilities, the Data Envelopment Analysis (DEA) is used to take into account the conventional selection criteria: price, delivery, quality and capacity. A set of Pareto-optimal suppliers is obtained from the combination of efficiencies and reliability scores. Finally, the decision maker chooses between the non-dominated suppliers. Obtained experiment results indicate the effectiveness of the proposed framework.

An application of data envelopment analysis for measuring the relative efficiency in banking industry

“…Data envelopment analysis (DEA) is one of the most popular techniques among both practitioners and scientists (Kuah et al, 2010;Cooper et al, 2011). The method has been applied for measuring technology (Khouja, 1995), measuring the performance of airports (Roghanian & Foroughi, 2010), supplier selection (Levary, 2008;Azar et al, 2011;Nourbakhsh et al, 2013) and heath care (Ghotbuee et al, 2012;Khani et al, 2012). Charnes et al (1978Charnes et al ( , 1985Charnes et al ( , 1990) are believed to be the first who introduced the idea of measuring non-financial units based on various inputs/outputs.…”

Multicriteria 3PL Selection with Risk Considerations

“…This methodology was validated in a Colombian company (Urbano y Muñoz, 2013). Multiobjective programming, DEA [27] Multiobjective programming and ANP [20] Neuronal network y DEA [22] Fuzzy multiobjective [28] Fuzy TOPSIS and MCGP [4] Multiobjective model and AHP [7] QFD and linear programming [5] QFD and DEA [11] This company is one of the largest and the most recognized in the health and beauty business.…”

Incorporating management opinion in green supplier selection model using quality function deployment and interactive fuzzy programming

“…This technique is beneficial when several approaches are combined to tackle complex supplier choice issues [ 64 – 66 ]. Some of the hybrid models are the integrated Data Envelopment Analysis-Artificial Intelligence (DEA-AI) and Data Envelopment Analysis-Artificial Neural Network (DEA-ANN) technique [ 67 ]. During the past years, a major research trend is seen in dealing with the uncertainties in the supplier selection problems.…”