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Application of Fuzzy Topsis and Taguchi Methods for Optimization Problems With Disruptive Risk: A Systematic Review
Abstract
Ranking and choosing research projects and analyzing experiments are usually difficult and complex responsibilities for professional research councils at universities and research centers. Its complexity stems from having more than one variable in each project, and the participation of many decision-makers in the ranking process and selection of research projects based on many variables. The fuzzy set theory provides the required flexibility to show the uncertainty about the lack of knowledge, and also it can manage the uncertainty in the real world that the values of criteria are not defined properly. For this purpose, in the environment where the criteria of research projects are vaguely defined, the ranking methods such as Taguchi, which can reduce the number of experiments and making process more efficient, can be used for quality design in designing and processing product. In this work, first of all, the authors review fuzzy TOPSIS technique and the Taguchi method as well; then they approach research efficiency and optimization of the level of effective parameters in an experiment.
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