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The green supplier selection (GSS) problem is a well-known strategy to outsource with respect to environmental protection. Although different applications of GSS have been proposed in the literature, the fuzzy five-objective GSS model has not been studied yet. This paper develops a multi-objective fuzzy linear programming model for a GSS problem, including 17 criteria, formed into 5 clusters while a hybrid fuzzy multi objective decision making (MODM) is employed to solve it. The aim of this paper is to select the best set of suppliers regarding optimal allocation of order quantities while demand and supplier's capacity are restricted. In the proposed hybrid solution algorithm, fuzzy decision making trial and evaluation laboratory approach is used to understand the interrelation among criteria, and fuzzy analytical network process (ANP) provides the criteria weights with respect to their dependencies. Then, a hybrid of fuzzy ANP and fuzzy multi-objective linear programming presents optimal order allocation among the selected suppliers, verified and compared with two other methods. Finally, the conclusion and future research are presented.Keywords Green supplier selection · Fuzzy analytical network process (ANP) · Fuzzy decision making trial and Evaluation laboratory (DEMATEL) · Order allocation · Fuzzy multi-objective linear programming (MOLP) · Weighted max-min operator

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Nowadays, many service provider organizations compete to survive and surpass other competitors in the world. They apply new techniques and instruments to identify and to prioritize important criteria for their customers to gain customer satisfaction. Banks, as one of the service provider organizations, are no exception. Quality plays essential role in banking industry and customer' gratification is considered as one of the major and essential goals in this field. Recognition and awareness regarding the customers' needs and requirements would facilitate providing satisfactory services. It could be said that improved understanding, accurate identification and prioritization of bank customers' requirements are the keys to success for bank managers. The present study aims to integrate two approaches of Quality Function Deployment (QFD) and Kano's model through implementation of Analytical Hierarchy Process (AHP). This study proposes a novel approach to identify and to analyze the priorities of bank customers' requirements. The results indicate that the priorities of bank customers are different before and after integration of Kano's Model in the planning matrix of QFD.

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Today green supply chain is considered all around the world and supplier selection has been changed regarding these green and carbon emission criteria, so green supplier selection has been a major problem in this area. In this study we use fuzzy time function to assist managers in green supplier selection under uncertainty and ambiguity. This function will consider derivation from the goal during the time and by using it, and we will be able to have the best supplier in every period after having some modification in legal limitations for green supplier selection criteria. We use a fuzzy TOPSIS to have better initial weighting in TODIM, a discrete multicriteria method based on prospect theory in uncertainty (known as TODIM in Portuguese) decision making method. The results indicated that our proposed approach can easily and effectively accommodate criteria with gains and loss functions during time and also by using this method we will have a more reasonable predict of our suppliers ranking in future and that will help us in future investment in these suppliers. Finally it has been shown in car industries in Iran.