نتایج جستجو برای: group decision making crisp topsis fuzzy topsis maintenance strategy sensitivity analysis
تعداد نتایج: 4541467 فیلتر نتایج به سال:
Most decision-making processes are dynamic. Critical decisions require multiple and interrelated time-constrained decisions within strongly uncertain and so complex scenarios. The proposed methodology (mixing Delphi, Fuzzy Cognitive Maps and TOPSIS) and is a step forward with regard to the classic tools used in scenarios-based decision-support. This proposal allows managing uncertainty for impr...
The layout design problem is a strategic issue and has a significant impact on the efficiency of a manufacturing system. Much of the existing layout design literature that uses a surrogate function for flow distance or for simplified objectives may be entrapped into local optimum; and subsequently lead to a poor layout design due to the multiple-attribute decision making (MADM) nature of a layo...
The technique for order preference by similarity to ideal solution (TOPSIS) is a well-known multi-attribute decision making (MADM) method that is used to identify the most attractive alternative solution among a finite set of alternatives based on the simultaneous minimization of the distance from an ideal solution (IS) and the maximization of the distance from the nadir solution (NS). We propo...
This paper proposes a method for ranking decision making units (DMUs) using some of the multiple criteria decision making / multiple attribute decision making (MCDM /MADM) techniques, namely, interval analytic hierarchy process (IAHP) and the technique for order preference by similarity to an ideal solution (TOPSIS). Since the efficiency score of unity is assigned to ...
Due to an increased awareness and significant environmental pressures from various stakeholders, companies have begun to realize the significance of incorporating green practices into their daily activities. This paper proposes a framework using Fuzzy TOPSIS to select green suppliers for a Brazilian electronics company; our framework is built on the criteria of green supply chain management (GS...
The theory of intuitionistic fuzzy set (IFS) is well suitable to deal with vagueness and hesitancy. In this study, we propose a new fuzzy TOPSIS decision making model using entropy weight for dealing with multiple criteria decision making (MCDM) problems under intuitionistic fuzzy environment. This model allows measuring the degree of satisfiability and the degree of non-satisfiability, respect...
The supplier selection process attracted a lot of attention in the business management literature. This process takes into consideration several quantitative and qualitative variables and is usually modeled as a multi-attribute decision making (MADM) problem. A recognized shortcoming in the literature of classical MADM methods is that they don’t permit the identification of interdependencies am...
Contractor selection is one of the most important aspects in construction contract. This paper suggests importance of various multi criteria decision making models for contractor selection problem in Indian context. The study includes identifying the different criteria for bid evaluation and the means by which different decision making models may be used to evaluate the contractors with respect...
This paper proposes a method for ranking decision making units (DMUs) using some of the multiple criteria decision making / multiple attribute decision making (MCDM /MADM) techniques, namely, interval analytic hierarchy process (IAHP) and the technique for order preference by similarity to an ideal solution (TOPSIS). Since the efficiency score of unity is assigned to ...
The evaluation and selection of reliable suppliers are an extremely important operational activity for any supply chain management. It is a hard problem since supplier typically multi-criteria decision-making involving several conflicting qualitative quantitative criteria on which the decision-maker’s knowledge usually vague imprecise. process may be biased while decision made by single expert ...
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