... hierarchy process Supply chain management Fuzzy sets The rules and regulations implemented by the governments and the increasing awareness of the stakeholders about the necessity of sustainable practices have resulted in the increased acceptance of the sustainable practices all over the world...

... rights only Uncertainty Quality function deployment Flexibility Supply chain management Fuzzy sets The rest of the paper is organised as follows. In Section 2 , the review of the literature on SCF, entrepreneurial orientation, and environmental uncertainty are given. It also presents...

... hierarchy process Artifical intelligence Fuzzy sets Object-oriented methods 20 08 2016 18 11 2016 29 11 2016 © Emerald Publishing Limited 2017 Emerald Publishing Limited Licensed re-use rights only The purpose of this paper is to propose a decision support system...

... to other researchers and the department members in any firm who are responsible for selecting the vendor. Cognition Supply chain management Vendors Analytic hierarchy process Dynamic model Vendor selection Fuzzy sets In today's highly competitive and interrelated manufacturing environment...

...M. Shamsuzzaman; A.M.M. Sharif Ullah; Erik L.J. Bohez This paper presents a computational framework that combines both fuzzy sets and analytical hierarchy process (AHP) for selecting the best‐ranked flexible manufacturing system from a number of feasible alternatives. Fuzzy sets are employed...

..., misdirection of implementation of improvement projects due to subjective evaluation of process performance can be reduced. A fuzzy set of quality measures is introduced to calculate numerical quality rating for processes. The model is simulated and experimented on with a conventional improvement implementation...

... a few studies address parameter optimization of the qualitative (or linguistic) response. The fuzzy set is a well‐known approach for dealing with the uncertainties of the linguistic description. Additionally, Taguchi’s quadratic quality loss function is an efficient technique to evaluate quality...

.... These requirements are fuzzified and represented by the relevant fuzzy sets in the relevant input fuzzy regions according to the knowledge held in K‐CA and K‐PA. The input fuzzy regions are then submitted to rule evaluation to allow the relations in the regions to be combined by merging the properties...