نتایج جستجو برای: topsis and linmap decision making
تعداد نتایج: 16881474 فیلتر نتایج به سال:
Many real-world decision making problems require multiple criteria which can be from different nature. This implies to define a heterogeneous context with different types of information that experts will use to provide their assessments. But sometimes, experts do not have enough knowledge or information to assess the criteria and they hesitate to express their assessments. Therefore, in this co...
As one of the emerging renewable resources, the use of photovoltaic cells has become a promise for offering clean and plentiful energy. The selection of a best photovoltaic cell for a promoter plays a significant role in aspect of maximizing income, minimizing costs and conferring high maturity and reliability, which is a typical multiple attribute decision making (MADM) problem. Although many ...
This paper is devoted to present Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method for multi-attribute group decision making under rough neutrosophic environment. The concept of rough neutrosophic set is a powerful mathematical tool to deal with uncertainty, indeterminacy and inconsistency. In this paper, a new approach for multi-attribute group decision making prob...
a basic assumption of madm methods such as saw and topsis is the statistical independence of criteria. violating this assumption would result in erroneous decisions. however, there are many cases in which criteria are dependent and based on this situation decision has to be made. in this paper, an approach based on the property of principal component analysis (pca) in producing independent vari...
risk response planning is one of the main phases in the project risk management and has major impacts on the success of a large-scale project. since projects are unique, and risks are dynamic through the life of the projects, it is necessary to formulate responses of the important risks. the conventional approaches tend to be less effective in dealing with the impreciseness of risk response pl...
Electronic commerce (EC) development takes place in a complex and dynamic environment that includes high levels of risk and uncertainty. This paper proposes a new method to assess the risks associated with EC development using multi-criteria decision-making techniques A model based on analytic hierarchy process (AHP) and the technique for order of preference by similarity to ideal solution (TOP...
This paper reports the study on the development of a ‘decision support system (DSS)’ software for cotton fibre grading and selection, and its applications in the textile spinning industry. Two multi-criteria decision making approaches, namely ‘analytic hierarchy process (AHP)’ and ‘technique for order preference by similarity to ideal solutions (TOPSIS)’, have been amalgamated in the developed ...
This paper extends the technique for order preference by similarity to ideal solution (TOPSIS) for solving multi-attribute group decision making (MAGDM) problems under Atanassov intuitionistic fuzzy set (IFS) environments. In this methodology, weights of attributes and ratings of alternatives on attributes are extracted from fuzziness inherent in decision data and making process and described u...
The impact of a near-Earth object (NEO) may release large amounts of energy and cause serious damage. Several NEO hazard studies conducted over the past few years provide forecasts, impact probabilities and assessment ratings, such as the Torino and Palermo scales. These high-risk NEO assessments involve several criteria, including impact energy, mass, and absolute magnitude. The main objective...
The fuzzy set has its own limitations due to the membership function only. does not describe negative aspects of an object. Fermatean covers complex is most effective tool for handling ambiguous and uncertain information. aim this research work develop new techniques decision-making based on numbers. First, we construct different aggregation operators numbers, using Einstein t-norms. We define ...
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