A multi-objective mathematical model integrating environmental concerns for supplier selection and order allocation based on fuzzy QFD in beverages industry

•A novel Fuzzy QFD model is proposed for determining the weights of the suppliers.•A stochastic multi-objective programming model is developed for order allocation.•The application of the model is shown in beverages industry.•Environmental factors in the QFD method, and one of the objectives are con...

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Vydané v:Expert systems with applications Ročník 92; s. 27 - 38
Hlavní autori: Babbar, Chirag, Amin, Saman Hassanzadeh
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: New York Elsevier Ltd 01.02.2018
Elsevier BV
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ISSN:0957-4174, 1873-6793
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Shrnutí:•A novel Fuzzy QFD model is proposed for determining the weights of the suppliers.•A stochastic multi-objective programming model is developed for order allocation.•The application of the model is shown in beverages industry.•Environmental factors in the QFD method, and one of the objectives are considered.•The multi-objective model is solved by three solution approaches. With the emerging trend of green supply chain management, supplier selection and order allocation based on green criteria have become very important in this competitive world. During the selection process of the eligible suppliers, qualitative as well as quantitative factors should be considered. In this paper, a novel mathematical model is developed to select a set of suppliers, and assign the order quantity. Due to the importance of environmental concerns, both qualitative and quantitative environmental criteria are taken into account in this research. The proposed model comprises two phases namely a two-stage QFD, and a stochastic multi-objective mathematical model. The stochastic (scenario) approach helps to manage the uncertainty in the order allocation process. Furthermore, trapezoidal fuzzy numbers are utilized to handle the vagueness in human thoughts. The application of the proposed model is shown in beverages industry.
Bibliografia:ObjectType-Article-1
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content type line 14
ISSN:0957-4174
1873-6793
DOI:10.1016/j.eswa.2017.09.041