Matching of technological forecasting technique to a technology using fuzzy multi-attribute decision-making methods: Case study from the aerospace industry

2021 ◽  
Vol 67 ◽  
pp. 101707
Author(s):  
Jalil Heidary Dahooie ◽  
Navid Mohammadi ◽  
Tugrul Daim ◽  
Amir Salar Vanaki ◽  
Edmundas Kazimieras Zavadskas
Keyword(s):  
Decision Making ◽  
Aerospace Industry ◽  
Technological Forecasting ◽  
Multi Attribute Decision Making

Fuzzy Analytic Hierarchy Process and Its Application to E-Marketplace Selection

2013 ◽  
pp. 26-44 ◽  
Author(s):  
Beyza Ahlatcioglu Ozkok ◽  
Elisa Pappalardo
Keyword(s):  
Decision Making ◽  
Analytic Hierarchy Process ◽  
Fuzzy Ahp ◽  
Multi Criteria Decision Making ◽  
Linguistic Variables ◽  
Analytic Hierarchy ◽  
Multi Attribute Decision Making ◽  
Electronic Parts ◽  
Hierarchy Process

Making decisions is a part of daily life. The nature of decision-making includes multiple and usually conflicting criteria. Multi Criteria Decision-Making (MCDM) problems are handled under two main headings: Multi Attribute Decision Making (MADM) and Multi Objective Decision Making (MODM). Analytic Hierarchy Process (AHP) is a widely used multi-criteria decision making approach and has successfully been applied to many practical problems. Traditional AHP requires exact or crisp judgments (numbers). However, due to the complexity and uncertainty involved in real world decision problems, decision makers might be more reluctant to provide crisp judgments than fuzzy ones. Furthermore, even when people use the same words, individual judgments of events are invariably subjective, and the interpretations that they attach to the same words may differ. This is why fuzzy numbers and fuzzy sets have been introduced to characterize linguistic variables. Here, the authors overview the most known fuzzy AHP approaches and their application, and they present a case study to select an e-marketplace for a firm, which produces and sells electronic parts of computers in Turkey.

Many-Attribute Decision Making Using Iterative Attribute Subsets

2016 ◽  
Author(s):  
Laura Ziegler ◽  
Kemper Lewis
Keyword(s):  
Decision Making ◽  
Large Scale ◽  
Design Space Exploration ◽  
Design Space ◽  
Space Exploration ◽  
Decision Problems ◽  
Trade Off ◽  
Current Design ◽  
Multi Attribute Decision Making

A unique set of cognitive and computational challenges arise in large-scale decision making, in relation to trade-off processing and design space exploration. While several multi-attribute decision making methods exist in the current design literature, many are insufficient or not fully explored for many-attribute decision problems of six or more attributes. To address this scaling in complexity, the methodology presented in this paper strategically elicits preferences over iterative attribute subsets while leveraging principles of the Hypothetical Equivalents and Inequivalents Method (HEIM). A case study demonstrates the effectiveness of the approach in the construction of a systematic representation of preferences and the convergence to a single ‘best’ alternative.

scholarly journals IMPROVING CONSISTENCY EVALUATION IN FUZZY MULTI-ATTRIBUTE PAIRWISE COMPARISON-BASED DECISION-MAKING METHODS

2014 ◽  
Vol 31 (04) ◽  
pp. 1450024 ◽  
Author(s):  
FARHAD SHAMS ◽  
SHERIF MOHAMED ◽  
AMINAH ROBINSON FAYEK
Keyword(s):  
Decision Making ◽  
Set Theory ◽  
Decision Model ◽  
Pairwise Comparison ◽  
Pairwise Comparisons ◽  
Linguistic Data ◽  
Multi Attribute Decision Making ◽  
Numeric Scale ◽  
Consistency Evaluation

A typical approach to handle the complexity of multi-faceted decision-making problems is to use multi-attribute decision-making (MADM) methods based on pairwise comparisons. Fuzzy set theory has also been employed to cope with the uncertainty and vagueness involved in conducting the comparisons between components of a decision model. An important issue regarding the reliability of the output is the consistency of pairwise comparisons provided by the decision maker(s). Using the MADM method developed by Lu et al. (2007) as a foundation, this paper proposes an algorithm for evaluating the consistency level of pairwise comparison matrices, where linguistic data are used. A crisp numeric scale has been introduced to consider the priority of linguistic data and to avoid the complexity of handling fuzzy calculations in consistency evaluation of pairwise comparison matrices. As an advantage, the proposed method of consistency evaluation is capable of assessing the degree of inconsistency among the pairwise comparisons. Therefore, the acceptance or rejection of the pairwise comparisons can be determined based on the desired degree of tolerance in accepting inconsistent judgments. An application of a revised MADM method is then demonstrated in a case study involving flood mitigation project selection in Australia.

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