文章基本信息

标题：Considering supply risk for supplier selection using an integrated framework of data envelopment analysis and neural networks
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作者：Nourbakhsh, V. ; Nourbakhsh, V. ; Ahmadi, A. 等
期刊名称：International Journal of Industrial Engineering Computations
印刷版ISSN：1923-2926
电子版ISSN：1923-2934
出版年度：2013
卷号：4
期号：2
页码：273-284
DOI：10.5267/j.ijiec.2013.01.001
语种：English
出版社：Growing Science Publishing Company
摘要：For many years, supplier selection as an important multi-criteria decision has attracted both the researchers and practitioners. Recently, high incidences of natural disasters, terrorism attacks, labor strikes, and other kinds of risks, also known as disruptions, indicate 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 is asked to determine the reliability of each procurement element (i.e., production, transportation, and communication) based on some proposed risk factors. Then, a distinct Multi-Layer Perceptron (MLP) network is trained to play the role of the expert opinion for estimating the reliability scores of each procurement. 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 is recommended to choose between the non-dominated suppliers. Obtained experiment results indicate the effectiveness of the proposed framework.
关键词：Data Envelopment Analysis; Disruption; Multi-Layer Perceptron; Supplier Selection; Supply Risk