An integrated Taguchi loss function–fuzzy cognitive map–MCGP with utility function approach for supplier selection problem

Abstract

Due to the effects of supplier evaluation and selection problem on the quality of products and companies’ business activities, supplier selection is considered as a strategic issue in organizations’ development plans. The purpose of this study is to provide an integrated framework for supplier selection problem regarding to the loss of criteria deviation from specification limits, causal relationships between criteria and the preferences of decision makers (DMs) in the supplier selection problem. Thus, in the first step, the loss of each criterion is calculated using Taguchi loss function (TLF), then fuzzy cognitive map (FCM) and hybrid learning algorithm are applied to determine criteria weights. Finally, considering outputs of TLF and FCM methods, multi-choice goal programming with utility function (MCGP-U) is used to select an optimal supplier and to increase the DMs’ expected utility values, simultaneously. The results of implementation of proposed framework based on the extended MCGP-U model on an active company in paint and coating industry show that delivery time criterion has the most effect and priority on suppliers’ evaluations. Also among six qualified suppliers, a supplier with the least total loss value and the most utility values is selected as the optimal supplier for the under consideration company.