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Erschienen in:
2016 | OriginalPaper | Buchkapitel
Fuzzy Topsis Method Associated with Improved Selection of Machines of High Productivity
verfasst von : Lourdes Margain, Alberto Ochoa, Oscar Castillo, Saúl González, Guadalupe Gutiérrez
Erschienen in: Distributed Computing and Artificial Intelligence, 13th International Conference
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This study combines Fuzzy Logic and multicriteria TOPSIS method for the selection, from three different alternatives, which machines of high productivity is more convenient to a construction company. The evaluation of each alternative is made through group decision making which identifies the most important criteria according to the requirements presented by the company. To assess the selected criteria in the TOPSIS method is weighted by a group of experts who, based on their experience and knowledge of this type of machinery, assess the relevance of these in the operation and functioning of the hydraulic excavator. Both qualitative and quantitative studies are used in this work, however the experts evaluate, through surveys based on Likert scale all the criteria in which they want to measure the perception. Data provided from the surveys is used for the construction and association of the groups of expert’s opinion through the use of fuzzy sets to avoid ambiguity problems of the linguistic variables.