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Analysis in Material Selection: Influence of Normalization Tools on COPRAS-G

Morteza Yazdani (), Ali Jahan () and Ed. Kazimieras Zavadskas ()
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Morteza Yazdani: Department of Business Management, Faculty of Social Sciences Universidad Europea de Madrid, Madrid, 28670, Spain
Ali Jahan: Department of Industrial Engineering, Semnan Branch Islamic Azad University, Semnan, Iran
Ed. Kazimieras Zavadskas: Department of Construction Technology and Management Vilnius Gediminas Technical University, Vilnius, Lithuania

ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH, 2017, vol. 51, issue 1, 59-74

Abstract: Multi criteria decision making (MCDM) methods algorithms are influenced by many parameters and variables as orientation of attributes, aggregation attitude, weights and normalization tools. Various MCDM methods find solution for decision problems using different normalization methods. Normalization process has an important role in decision process and can modify the ranking and final decision. Due to uncertainty associated with data in decision making about materials and design, COPRAS method with interval numbers (COPRAS-G) was recognized as a promising approach in this regard. This paper intends to apply COPRAS-G method in several specific material evaluation studies. Normalization tools are positioned in COPRAS method to check the effect of each tool. Two examples of material and design selection projects are recognized suitable for this study. The results show depending on the number of criteria and number of alternatives material, ranking can be changed when a different normalization tools are considered. This help designers and engineers to achieve a compromise on design decision making process, especially when the material properties and design performance criteria are affected from stochastic nature of design and manufacturing parameters

Keywords: COPRAS-G; interval data; materials selection; MCDM; Normalization tools. (search for similar items in EconPapers)
JEL-codes: C44 C61 C63 L6 (search for similar items in EconPapers)
Date: 2017
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