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首页> 外文期刊>Journal of ambient intelligence and humanized computing >Neutrosophic AHP-Delphi Group decision making model based on trapezoidal neutrosophic numbers
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Neutrosophic AHP-Delphi Group decision making model based on trapezoidal neutrosophic numbers

机译：基于梯形中智数的中智AHP-Delphi群决策模型

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The main objective of this research is to study the integration of Analytic Hierarchy Process (AHP) into Delphi framework in neutrosophic environment and present a new technique for checking consistency and calculating consensus degree of expert’s opinions. In some pragmatism bearings, the experts might be not able to assign deterministic evaluation values to the comparison judgments due to his/her confined knowledge or the differences of individual judgments in group decision making. To overcome these challenges, we have used neutrosophic set theory to handle the integration of AHP into Delphi framework, where each pairwise comparison judgment is symbolized as a trapezoidal neutrosophic number. The power of AHP is enhanced by adding Delphi technique, since it can reduce noise which result from focusing on group and/or individual interests rather than concentriciting on problem disband and it also increase consensus degree about ideas. Obtaining a consistent trapezoidal neutrosophic preference relation is very difficult in decision making process because in creating a consistent trapezoidal preference relation; each expert should make $$frac{{n times left( {n - 1} right)}}{2}$$ n × n - 1 2 consistent judgments for $$n$$ n alternatives. When the number of alternatives is increasing, the workload of giving judgments for the experts is heavy and it makes them tired and leads to inconsistent judgments. In the proposed model,experts will focus only on $$left( {n - 1} right)$$ n - 1 restricted judgments and this also enhances the performance of AHP over the traditional version that is proposed by Saaty. A real life example is developed based on expert opinions about evaluation process of many international search engines. The problem is solved to show the validation of the suggested method in neutrosophic path.
机译：本研究的主要目的是研究在中智环境下将层次分析法（AHP）集成到Delphi框架中，并提出一种检查专家意见的一致性和计算共识度的新技术。在某些实用主义方面，由于专家的局限性知识或小组决策中的个人判断差异，专家可能无法将确定性评估值分配给比较判断。为了克服这些挑战，我们使用了中智集合论来处理AHP到Delphi框架的集成，其中每个成对比较判断都被表示为梯形中智数。 AHP的功能通过添加Delphi技术得以增强，因为它可以减少由于关注小组和/或个人利益而不是集中于解决问题而导致的噪音，并且还可以提高对观点的共识程度。在决策过程中，要获得一致的梯形中智偏好关系是非常困难的，因为要创建一致的梯形偏好关系。每个专家都应做出$$ frac {{n次左移（{n-1}右}}} {2} $$ n×n-1 2个对$$ n $$ n备选方案的一致判断。当替代方案的数量增加时，为专家做出判断的工作量就很大，这会使他们感到疲倦，并导致判断不一致。在提出的模型中，专家将仅关注$$ left（{n-1} right）$$ n-1限制的判断，并且与Saaty提出的传统版本相比，这也提高了AHP的性能。根据有关许多国际搜索引擎评估过程的专家意见，开发了一个真实的例子。解决了该问题，以证明所建议方法在中智路径中的有效性。

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